pcl Namespace Reference

Namespaces
	common
	ComparisonOps
	console
	cuda
	deprecated
	detail
	device
	distances
	experimental
	face_detection
	features
	fields
	filters
	geometry
	gpu
	internal
	io
	ism
	keypoints
	kinfuLS
	ndt2d
	occlusion_reasoning
	octree
	outofcore
	people
	poisson
	recognition
	registration
	search
	segmentation
	surface
	test
	test_macros.h provide helper macros for testing vectors, matrices etc.
	texture_mapping
	tracking
	traits
	utils
	visualization

Classes
struct	PointXYZIEdge
	Point cloud containing edge information. More...
class	Convolution
	A 2D convolution class. More...
class	Edge
class	kernel
class	Keypoint
	Keypoint represents the base class for key points. More...
class	Morphology
class	CloudIterator
	Iterator class for point clouds with or without given indices. More...
class	ConstCloudIterator
	Iterator class for point clouds with or without given indices. More...
class	BivariatePolynomialT
	This represents a bivariate polynomial and provides some functionality for it. More...
struct	NdCentroidFunctor
	Helper functor structure for n-D centroid estimation. More...
class	CentroidPoint
	A generic class that computes the centroid of points fed to it. More...
class	ColorLUT
struct	NdConcatenateFunctor
	Helper functor structure for concatenate. More...
class	PointCloud
	PointCloud represents the base class in PCL for storing collections of 3D points. More...
class	FeatureHistogram
	Type for histograms for computing mean and variance of some floats. More...
class	GaussianKernel
	Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel. More...
class	PCA
	Principal Component analysis (PCA) class. More...
class	PiecewiseLinearFunction
	This provides functionalities to efficiently return values for piecewise linear function. More...
class	PolynomialCalculationsT
	This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials. More...
class	PosesFromMatches
	calculate 3D transformation based on point correspondences More...
class	Synchronizer
	/brief This template class synchronizes two data streams of different types. More...
class	StopWatch
	Simple stopwatch. More...
class	ScopeTime
	Class to measure the time spent in a scope. More...
class	EventFrequency
	A helper class to measure frequency of a certain event. More...
class	TimeTrigger
	Timer class that invokes registered callback methods periodically. More...
class	TransformationFromCorrespondences
	Calculates a transformation based on corresponding 3D points. More...
class	VectorAverage
	Calculates the weighted average and the covariance matrix. More...
struct	Correspondence
	Correspondence represents a match between two entities (e.g., points, descriptors, etc). More...
struct	PointCorrespondence3D
	Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g. More...
struct	PointCorrespondence6D
	Representation of a (possible) correspondence between two points (e.g. More...
class	PCLException
	A base class for all pcl exceptions which inherits from std::runtime_error. More...
class	InvalidConversionException
	An exception that is thrown when a PCLPointCloud2 message cannot be converted into a PCL type. More...
class	IsNotDenseException
	An exception that is thrown when a PointCloud is not dense but is attempted to be used as dense. More...
class	InvalidSACModelTypeException
	An exception that is thrown when a sample consensus model doesn't have the correct number of samples defined in model_types.h. More...
class	IOException
	An exception that is thrown during an IO error (typical read/write errors) More...
class	InitFailedException
	An exception thrown when init can not be performed should be used in all the PCLBase class inheritants. More...
class	UnorganizedPointCloudException
	An exception that is thrown when an organized point cloud is needed but not provided. More...
class	KernelWidthTooSmallException
	An exception that is thrown when the kernel size is too small. More...
class	UnhandledPointTypeException
class	ComputeFailedException
class	BadArgumentException
	An exception that is thrown when the arguments number or type is wrong/unhandled. More...
struct	for_each_type_impl
struct	for_each_type_impl< false >
struct	intersect
class	DefaultIterator
class	IteratorIdx
struct	_PointXYZ
struct	PointXYZ
	A point structure representing Euclidean xyz coordinates. More...
struct	_RGB
struct	RGB
	A structure representing RGB color information. More...
struct	_Intensity
struct	Intensity
	A point structure representing the grayscale intensity in single-channel images. More...
struct	_Intensity8u
struct	Intensity8u
	A point structure representing the grayscale intensity in single-channel images. More...
struct	_Intensity32u
struct	Intensity32u
	A point structure representing the grayscale intensity in single-channel images. More...
struct	_PointXYZI
	A point structure representing Euclidean xyz coordinates, and the intensity value. More...
struct	PointXYZI
struct	_PointXYZL
struct	PointXYZL
struct	Label
struct	_PointXYZRGBA
struct	PointXYZRGBA
	A point structure representing Euclidean xyz coordinates, and the RGBA color. More...
struct	_PointXYZRGB
struct	_PointXYZRGBL
struct	PointXYZRGB
	A point structure representing Euclidean xyz coordinates, and the RGB color. More...
struct	PointXYZRGBL
struct	_PointXYZLAB
struct	PointXYZLAB
	A point structure representing Euclidean xyz coordinates, and the CIELAB color. More...
struct	_PointXYZHSV
struct	PointXYZHSV
struct	PointXY
	A 2D point structure representing Euclidean xy coordinates. More...
struct	PointUV
	A 2D point structure representing pixel image coordinates. More...
struct	InterestPoint
	A point structure representing an interest point with Euclidean xyz coordinates, and an interest value. More...
struct	_Normal
struct	Normal
	A point structure representing normal coordinates and the surface curvature estimate. More...
struct	_Axis
struct	Axis
	A point structure representing an Axis using its normal coordinates. More...
struct	_PointNormal
struct	PointNormal
	A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More...
struct	_PointXYZRGBNormal
struct	PointXYZRGBNormal
	A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate. More...
struct	_PointXYZINormal
struct	PointXYZINormal
	A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate. More...
struct	_PointXYZLNormal
struct	PointXYZLNormal
	A point structure representing Euclidean xyz coordinates, a label, together with normal coordinates and the surface curvature estimate. More...
struct	_PointWithRange
struct	PointWithRange
	A point structure representing Euclidean xyz coordinates, padded with an extra range float. More...
struct	_PointWithViewpoint
struct	PointWithViewpoint
	A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen. More...
struct	MomentInvariants
	A point structure representing the three moment invariants. More...
struct	PrincipalRadiiRSD
	A point structure representing the minimum and maximum surface radii (in meters) computed using RSD. More...
struct	Boundary
	A point structure representing a description of whether a point is lying on a surface boundary or not. More...
struct	PrincipalCurvatures
	A point structure representing the principal curvatures and their magnitudes. More...
struct	PFHSignature125
	A point structure representing the Point Feature Histogram (PFH). More...
struct	PFHRGBSignature250
	A point structure representing the Point Feature Histogram with colors (PFHRGB). More...
struct	PPFSignature
	A point structure for storing the Point Pair Feature (PPF) values. More...
struct	CPPFSignature
	A point structure for storing the Point Pair Feature (CPPF) values. More...
struct	PPFRGBSignature
	A point structure for storing the Point Pair Color Feature (PPFRGB) values. More...
struct	NormalBasedSignature12
	A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More...
struct	ShapeContext1980
	A point structure representing a Shape Context. More...
struct	UniqueShapeContext1960
	A point structure representing a Unique Shape Context. More...
struct	SHOT352
	A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape only. More...
struct	SHOT1344
	A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape+color. More...
struct	_ReferenceFrame
	A structure representing the Local Reference Frame of a point. More...
struct	ReferenceFrame
struct	FPFHSignature33
	A point structure representing the Fast Point Feature Histogram (FPFH). More...
struct	VFHSignature308
	A point structure representing the Viewpoint Feature Histogram (VFH). More...
struct	GRSDSignature21
	A point structure representing the Global Radius-based Surface Descriptor (GRSD). More...
struct	BRISKSignature512
	A point structure representing the Binary Robust Invariant Scalable Keypoints (BRISK). More...
struct	ESFSignature640
	A point structure representing the Ensemble of Shape Functions (ESF). More...
struct	GASDSignature512
	A point structure representing the Globally Aligned Spatial Distribution (GASD) shape descriptor. More...
struct	GASDSignature984
	A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor. More...
struct	GASDSignature7992
	A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor. More...
struct	GFPFHSignature16
	A point structure representing the GFPFH descriptor with 16 bins. More...
struct	Narf36
	A point structure representing the Narf descriptor. More...
struct	BorderDescription
	A structure to store if a point in a range image lies on a border between an obstacle and the background. More...
struct	IntensityGradient
	A point structure representing the intensity gradient of an XYZI point cloud. More...
struct	Histogram
	A point structure representing an N-D histogram. More...
struct	_PointWithScale
struct	PointWithScale
	A point structure representing a 3-D position and scale. More...
struct	_PointSurfel
struct	PointSurfel
	A surfel, that is, a point structure representing Euclidean xyz coordinates, together with normal coordinates, a RGBA color, a radius, a confidence value and the surface curvature estimate. More...
struct	_PointDEM
struct	PointDEM
	A point structure representing Digital Elevation Map. More...
struct	ModelCoefficients
class	PCLBase
	PCL base class. More...
class	PCLBase< pcl::PCLPointCloud2 >
struct	PCLHeader
struct	PCLImage
struct	PCLPointCloud2
struct	PCLPointField
struct	FieldMatches
struct	NdCopyEigenPointFunctor
	Helper functor structure for copying data between an Eigen type and a PointT. More...
struct	NdCopyPointEigenFunctor
	Helper functor structure for copying data between an Eigen type and a PointT. More...
class	PointRepresentation
	PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensional vector. More...
class	DefaultPointRepresentation
	DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types. More...
class	DefaultFeatureRepresentation
	DefaulFeatureRepresentation extends PointRepresentation and is intended to be used when defining the default behavior for feature descriptor types (i.e., copy each element of each field into a float array). More...
class	DefaultPointRepresentation< PointXYZ >
class	DefaultPointRepresentation< PointXYZI >
class	DefaultPointRepresentation< PointNormal >
class	DefaultPointRepresentation< PFHSignature125 >
class	DefaultPointRepresentation< PFHRGBSignature250 >
class	DefaultPointRepresentation< PPFSignature >
class	DefaultPointRepresentation< FPFHSignature33 >
class	DefaultPointRepresentation< VFHSignature308 >
class	DefaultPointRepresentation< GASDSignature512 >
class	DefaultPointRepresentation< GASDSignature984 >
class	DefaultPointRepresentation< GASDSignature7992 >
class	DefaultPointRepresentation< Narf36 >
class	DefaultPointRepresentation< NormalBasedSignature12 >
class	DefaultPointRepresentation< ShapeContext1980 >
class	DefaultPointRepresentation< UniqueShapeContext1960 >
class	DefaultPointRepresentation< SHOT352 >
class	DefaultPointRepresentation< SHOT1344 >
class	CustomPointRepresentation
	CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More...
struct	PointIndices
struct	PolygonMesh
class	BearingAngleImage
	class BearingAngleImage is used as an interface to generate Bearing Angle(BA) image. More...
class	RangeImage
	RangeImage is derived from pcl/PointCloud and provides functionalities with focus on situations where a 3D scene was captured from a specific view point. More...
class	RangeImagePlanar
	RangeImagePlanar is derived from the original range image and differs from it because it's not a spherical projection, but using a projection plane (as normal cameras do), therefore being better applicable for range sensors that already provide a range image by themselves (stereo cameras, ToF-cameras), so that a conversion to point cloud and then to a spherical range image becomes unnecessary. More...
class	RangeImageSpherical
	RangeImageSpherical is derived from the original range image and uses a slightly different spherical projection. More...
struct	TexMaterial
struct	TextureMesh
struct	CopyIfFieldExists
	A helper functor that can copy a specific value if the given field exists. More...
struct	SetIfFieldExists
	A helper functor that can set a specific value in a field if the field exists. More...
struct	has_custom_allocator
	Tests at compile time if type T has a custom allocator. More...
struct	Vertices
	Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More...
class	OrganizedNeighborSearch
	OrganizedNeighborSearch class More...
class	ShapeContext3DEstimation
	ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
class	BOARDLocalReferenceFrameEstimation
	BOARDLocalReferenceFrameEstimation implements the BOrder Aware Repeatable Directions algorithm for local reference frame estimation as described here: More...
class	BoundaryEstimation
	BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More...
class	BRISK2DEstimation
	Implementation of the BRISK-descriptor, based on the original code and paper reference by. More...
class	CPPFEstimation
	Class that calculates the "surflet" features for each pair in the given pointcloud. More...
class	CRHEstimation
	CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
class	CVFHEstimation
	CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
class	DifferenceOfNormalsEstimation
	A Difference of Normals (DoN) scale filter implementation for point cloud data. More...
class	ESFEstimation
	ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points. More...
class	Feature
	Feature represents the base feature class. More...
class	FeatureFromNormals
class	FeatureFromLabels
class	FeatureWithLocalReferenceFrames
	FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint. More...
class	FLARELocalReferenceFrameEstimation
	FLARELocalReferenceFrameEstimation implements the Fast LocAl Reference framE algorithm for local reference frame estimation as described here: More...
class	FPFHEstimation
	FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals. More...
class	FPFHEstimationOMP
	FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More...
class	GASDEstimation
	GASDEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ data. More...
class	GASDColorEstimation
	GASDColorEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ and RGB data. More...
class	GFPFHEstimation
	GFPFHEstimation estimates the Global Fast Point Feature Histogram (GFPFH) descriptor for a given point cloud dataset containing points and labels. More...
class	GRSDEstimation
	GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals. More...
struct	IntegralImageTypeTraits
struct	IntegralImageTypeTraits< float >
struct	IntegralImageTypeTraits< char >
struct	IntegralImageTypeTraits< short >
struct	IntegralImageTypeTraits< unsigned short >
struct	IntegralImageTypeTraits< unsigned char >
struct	IntegralImageTypeTraits< int >
struct	IntegralImageTypeTraits< unsigned int >
class	IntegralImage2D
	Determines an integral image representation for a given organized data array. More...
class	IntegralImage2D< DataType, 1 >
	partial template specialization for integral images with just one channel. More...
class	IntegralImageNormalEstimation
	Surface normal estimation on organized data using integral images. More...
class	IntensityGradientEstimation
	IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values. More...
class	IntensitySpinEstimation
	IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud dataset containing points and intensity. More...
class	LinearLeastSquaresNormalEstimation
	Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation. More...
class	MomentInvariantsEstimation
	MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point. More...
class	MomentOfInertiaEstimation
	Implements the method for extracting features based on moment of inertia. More...
class	MultiscaleFeaturePersistence
	Generic class for extracting the persistent features from an input point cloud It can be given any Feature estimator instance and will compute the features of the input over a multiscale representation of the cloud and output the unique ones over those scales. More...
class	Narf
	NARF (Normal Aligned Radial Features) is a point feature descriptor type for 3D data. More...
class	NarfDescriptor
	Computes NARF feature descriptors for points in a range image See B. More...
class	NormalEstimation
	NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point. More...
class	NormalEstimationOMP
	NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard. More...
class	NormalBasedSignatureEstimation
	Normal-based feature signature estimation class. More...
class	OrganizedEdgeBase
	OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals, and OrganizedEdgeFromRGBNormals find 3D edges from an organized point cloud data. More...
class	OrganizedEdgeFromRGB
class	OrganizedEdgeFromNormals
class	OrganizedEdgeFromRGBNormals
class	OURCVFHEstimation
	OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset given XYZ data and normals, as presented in: More...
class	PFHEstimation
	PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
class	PFHRGBEstimation
	Similar to the Point Feature Histogram descriptor, but also takes color into account. More...
class	PPFEstimation
	Class that calculates the "surflet" features for each pair in the given pointcloud. More...
class	PPFRGBEstimation
class	PPFRGBRegionEstimation
class	PrincipalCurvaturesEstimation
	PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More...
class	RangeImageBorderExtractor
	Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background. More...
class	RIFTEstimation
	RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity. More...
class	ROPSEstimation
	This class implements the method for extracting RoPS features presented in the article "Rotational Projection Statistics for 3D Local Surface Description and Object Recognition" by Yulan Guo, Ferdous Sohel, Mohammed Bennamoun, Min Lu and Jianwei Wan. More...
class	RSDEstimation
	RSDEstimation estimates the Radius-based Surface Descriptor (minimal and maximal radius of the local surface's curves) for a given point cloud dataset containing points and normals. More...
class	SHOTEstimationBase
	SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
class	SHOTEstimation
	SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
class	SHOTColorEstimation
	SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors. More...
class	SHOTLocalReferenceFrameEstimation
	SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
class	SHOTLocalReferenceFrameEstimationOMP
	SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
class	SHOTEstimationOMP
	SHOTEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More...
class	SHOTColorEstimationOMP
	SHOTColorEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors, in parallel, using the OpenMP standard. More...
class	SpinImageEstimation
	Estimates spin-image descriptors in the given input points. More...
class	StatisticalMultiscaleInterestRegionExtraction
	Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More...
class	UniqueShapeContext
	UniqueShapeContext implements the Unique Shape Context Descriptor described here: More...
class	VFHEstimation
	VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. More...
struct	xNdCopyEigenPointFunctor
	Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
struct	xNdCopyPointEigenFunctor
	Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
class	ApproximateVoxelGrid
	ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	BilateralFilter
	A bilateral filter implementation for point cloud data. More...
class	BoxClipper3D
	Implementation of a box clipper in 3D. Actually it allows affine transformations, thus any parallelepiped in general pose. The affine transformation is used to transform the point before clipping it using a cube centered at origin and with an extend of -1 to +1 in each dimension. More...
class	Clipper3D
	Base class for 3D clipper objects. More...
class	PointDataAtOffset
	A datatype that enables type-correct comparisons. More...
class	ComparisonBase
	The (abstract) base class for the comparison object. More...
class	FieldComparison
	The field-based specialization of the comparison object. More...
class	PackedRGBComparison
	A packed rgb specialization of the comparison object. More...
class	PackedHSIComparison
	A packed HSI specialization of the comparison object. More...
class	TfQuadraticXYZComparison
	A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0). More...
class	ConditionBase
	Base condition class. More...
class	ConditionAnd
	AND condition. More...
class	ConditionOr
	OR condition. More...
class	ConditionalRemoval
	ConditionalRemoval filters data that satisfies certain conditions. More...
class	CovarianceSampling
	Point Cloud sampling based on the 6D covariances. More...
class	CropBox
	CropBox is a filter that allows the user to filter all the data inside of a given box. More...
class	CropBox< pcl::PCLPointCloud2 >
	CropBox is a filter that allows the user to filter all the data inside of a given box. More...
class	CropHull
	Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes. More...
class	ExtractIndices
	ExtractIndices extracts a set of indices from a point cloud. More...
class	ExtractIndices< pcl::PCLPointCloud2 >
	ExtractIndices extracts a set of indices from a point cloud. More...
class	FarthestPointSampling
	FarthestPointSampling applies farthest point sampling using euclidean distance, starting with a random point, utilizing a naive method. More...
class	FastBilateralFilter
	Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
class	FastBilateralFilterOMP
	Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
class	Filter
	Filter represents the base filter class. More...
class	Filter< pcl::PCLPointCloud2 >
	Filter represents the base filter class. More...
class	FilterIndices
	FilterIndices represents the base class for filters that are about binary point removal. More...
class	FilterIndices< pcl::PCLPointCloud2 >
	FilterIndices represents the base class for filters that are about binary point removal. More...
class	FrustumCulling
	FrustumCulling filters points inside a frustum given by pose and field of view of the camera. More...
class	GridMinimum
	GridMinimum assembles a local 2D grid over a given PointCloud, and downsamples the data. More...
class	LocalMaximum
	LocalMaximum downsamples the cloud, by eliminating points that are locally maximal. More...
class	MedianFilter
	Implementation of the median filter. More...
class	ModelOutlierRemoval
	ModelOutlierRemoval filters points in a cloud based on the distance between model and point. More...
class	NormalRefinement
	Normal vector refinement class More...
class	NormalSpaceSampling
	NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point. More...
class	PassThrough
	PassThrough passes points in a cloud based on constraints for one particular field of the point type. More...
class	PassThrough< pcl::PCLPointCloud2 >
	PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More...
class	PlaneClipper3D
	Implementation of a plane clipper in 3D. More...
class	ProjectInliers
	ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
class	ProjectInliers< pcl::PCLPointCloud2 >
	ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
class	RadiusOutlierRemoval
	RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have. More...
class	RadiusOutlierRemoval< pcl::PCLPointCloud2 >
	RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain search radius is smaller than a given K. More...
class	RandomSample
	RandomSample applies a random sampling with uniform probability. More...
class	RandomSample< pcl::PCLPointCloud2 >
	RandomSample applies a random sampling with uniform probability. More...
class	SamplingSurfaceNormal
	SamplingSurfaceNormal divides the input space into grids until each grid contains a maximum of N points, and samples points randomly within each grid. More...
class	ShadowPoints
	ShadowPoints removes the ghost points appearing on edge discontinuties More...
class	StatisticalOutlierRemoval
	StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
class	StatisticalOutlierRemoval< pcl::PCLPointCloud2 >
	StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
class	UniformSampling
	UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	VoxelGrid
	VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	VoxelGrid< pcl::PCLPointCloud2 >
	VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	VoxelGridCovariance
	A searchable voxel structure containing the mean and covariance of the data. More...
class	VoxelGridLabel
class	VoxelGridOcclusionEstimation
	VoxelGrid to estimate occluded space in the scene. More...
class	LineIterator
	Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm. More...
class	OrganizedIndexIterator
	base class for iterators on 2-dimensional maps like images/organized clouds etc. More...
class	PlanarPolygon
	PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space. More...
class	TSDFVolume
class	AdaptiveRangeCoder
	AdaptiveRangeCoder compression class More...
class	StaticRangeCoder
	StaticRangeCoder compression class More...
class	ASCIIReader
	Ascii Point Cloud Reader. More...
class	DavidSDKGrabber
	Grabber for davidSDK structured light compliant devices. More...
class	DepthSenseGrabber
	Grabber for DepthSense devices (e.g. More...
class	DinastGrabber
	Grabber for DINAST devices (i.e., IPA-1002, IPA-1110, IPA-2001) More...
class	EnsensoGrabber
	Grabber for IDS-Imaging Ensenso's devices. More...
class	FileGrabber
	FileGrabber provides a container-style interface for grabbers which operate on fixed-size input. More...
class	FileReader
	Point Cloud Data (FILE) file format reader interface. More...
class	FileWriter
	Point Cloud Data (FILE) file format writer. More...
class	Grabber
	Grabber interface for PCL 1.x device drivers. More...
class	HDLGrabber
	Grabber for the Velodyne High-Definition-Laser (HDL) More...
class	IFSReader
	Indexed Face set (IFS) file format reader. More...
class	IFSWriter
	Point Cloud Data (IFS) file format writer. More...
class	ImageGrabberBase
	Base class for Image file grabber. More...
class	ImageGrabber
class	SynchronizedQueue
class	MTLReader
class	OBJReader
class	ONIGrabber
	A simple ONI grabber. More...
class	OpenNIGrabber
	Grabber for OpenNI devices (i.e., Primesense PSDK, Microsoft Kinect, Asus XTion Pro/Live) More...
class	PCDGrabberBase
	Base class for PCD file grabber. More...
class	PCDGrabber
class	PCDReader
	Point Cloud Data (PCD) file format reader. More...
class	PCDWriter
	Point Cloud Data (PCD) file format writer. More...
class	PLYReader
	Point Cloud Data (PLY) file format reader. More...
class	PLYWriter
	Point Cloud Data (PLY) file format writer. More...
class	RealSense2Grabber
	Grabber for Intel Realsense 2 SDK devices (D400 series) More...
class	RealSenseGrabber
class	RobotEyeGrabber
	Grabber for the Ocular Robotics RobotEye sensor. More...
class	TimGrabber
class	VLPGrabber
	Grabber for the Velodyne LiDAR (VLP), based on the Velodyne High Definition Laser (HDL) More...
class	KdTree
	KdTree represents the base spatial locator class for kd-tree implementations. More...
class	KdTreeFLANN
	KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
class	AgastKeypoint2DBase
	Detects 2D AGAST corner points. More...
class	AgastKeypoint2D
	Detects 2D AGAST corner points. More...
class	AgastKeypoint2D< pcl::PointXYZ, pcl::PointUV >
	Detects 2D AGAST corner points. More...
class	BriskKeypoint2D
	Detects BRISK interest points based on the original code and paper reference by. More...
class	HarrisKeypoint2D
	HarrisKeypoint2D detects Harris corners family points. More...
class	HarrisKeypoint3D
	HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals. More...
class	HarrisKeypoint6D
	Keypoint detector for detecting corners in 3D (XYZ), 2D (intensity) AND mixed versions of these. More...
class	ISSKeypoint3D
	ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud. More...
class	NarfKeypoint
	NARF (Normal Aligned Radial Feature) keypoints. More...
struct	SIFTKeypointFieldSelector
struct	SIFTKeypointFieldSelector< PointNormal >
struct	SIFTKeypointFieldSelector< PointXYZRGB >
struct	SIFTKeypointFieldSelector< PointXYZRGBA >
class	SIFTKeypoint
	SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More...
class	SmoothedSurfacesKeypoint
	Based on the paper: Xinju Li and Igor Guskov Multi-scale features for approximate alignment of point-based surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria. More...
class	SUSANKeypoint
	SUSANKeypoint implements a RGB-D extension of the SUSAN detector including normal directions variation in top of intensity variation. More...
class	TrajkovicKeypoint2D
	TrajkovicKeypoint2D implements Trajkovic and Hedley corner detector on organized point cloud using intensity information. More...
class	TrajkovicKeypoint3D
	TrajkovicKeypoint3D implements Trajkovic and Hedley corner detector on point cloud using geometric information. More...
class	BranchEstimator
	Interface for branch estimators. More...
class	BinaryTreeThresholdBasedBranchEstimator
	Branch estimator for binary trees where the branch is computed only from the threshold. More...
class	TernaryTreeMissingDataBranchEstimator
	Branch estimator for ternary trees where one branch is used for missing data (indicated by flag != 0). More...
class	DenseCrf
class	DecisionForest
	Class representing a decision forest. More...
class	DecisionForestEvaluator
	Utility class for evaluating a decision forests. More...
class	DecisionForestTrainer
	Trainer for decision trees. More...
class	DecisionTree
	Class representing a decision tree. More...
class	DecisionTreeTrainerDataProvider
class	DecisionTreeEvaluator
	Utility class for evaluating a decision tree. More...
class	DecisionTreeTrainer
	Trainer for decision trees. More...
class	FeatureHandler
	Utility class interface which is used for creating and evaluating features. More...
class	Fern
	Class representing a Fern. More...
class	FernEvaluator
	Utility class for evaluating a fern. More...
class	FernTrainer
	Trainer for a Fern. More...
class	Kmeans
	K-means clustering. More...
class	MultiChannel2DComparisonFeature
	Feature for comparing two sample points in 2D multi-channel data. More...
class	MultiChannel2DComparisonFeatureHandler
	Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
class	ScaledMultiChannel2DComparisonFeatureHandler
	Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
class	ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator
class	MultiChannel2DData
	Holds two-dimensional multi-channel data. More...
class	MultiChannel2DDataSet
	Holds a set of two-dimensional multi-channel data. More...
struct	MultipleData2DExampleIndex
	Example index for a set of 2D data blocks. More...
class	PairwisePotential
class	Permutohedral
	Implementation of a high-dimensional gaussian filtering using the permutohedral lattice. More...
class	HashTableOLD
class	PointXY32f
	2D point with float x- and y-coordinates. More...
class	PointXY32i
	2D point with integer x- and y-coordinates. More...
class	RegressionVarianceNode
	Node for a regression trees which optimizes variance. More...
class	RegressionVarianceStatsEstimator
	Statistics estimator for regression trees which optimizes variance. More...
class	StatsEstimator
	Class interface for gathering statistics for decision tree learning. More...
struct	SVMParam
	The structure stores the parameters for the classificationa nd must be initialized and passed to the training method pcl::SVMTrain. More...
struct	SVMModel
	The structure initialize a model created by the SVM (Support Vector Machines) classifier (pcl::SVMTrain). More...
struct	SVMDataPoint
	The structure initialize a single feature value for the classification using SVM (Support Vector Machines). More...
struct	SVMData
	The structure stores the features and the label of a single sample which has to be used for the training or the classification of the SVM (Support Vector Machines). More...
class	SVM
	Base class for SVM SVM (Support Vector Machines). More...
class	SVMTrain
	SVM (Support Vector Machines) training class for the SVM machine learning. More...
class	SVMClassify
	SVM (Support Vector Machines) classification of a dataset. More...
class	CorrespondenceGrouping
	Abstract base class for Correspondence Grouping algorithms. More...
class	GeometricConsistencyGrouping
	Class implementing a 3D correspondence grouping enforcing geometric consistency among feature correspondences. More...
class	Hough3DGrouping
	Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene. More...
class	ColorGradientDOTModality
class	ColorGradientModality
	Modality based on max-RGB gradients. More...
class	ColorModality
class	CRHAlignment
	CRHAlignment uses two Camera Roll Histograms (CRH) to find the roll rotation that aligns both views. More...
struct	DenseQuantizedSingleModTemplate
struct	DenseQuantizedMultiModTemplate
class	DistanceMap
	Represents a distance map obtained from a distance transformation. More...
class	DOTModality
struct	DOTMODDetection
class	DOTMOD
	Template matching using the DOTMOD approach. More...
class	RFFaceDetectorTrainer
class	GreedyVerification
	A greedy hypothesis verification method. More...
class	GlobalHypothesesVerification
	A hypothesis verification method proposed in "A Global Hypotheses Verification Method for 3D Object Recognition", A. More...
class	PapazovHV
	A hypothesis verification method proposed in "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes", C. More...
class	HypothesisVerification
	Abstract class for hypotheses verification methods. More...
struct	ISMPeak
	This struct is used for storing peak. More...
struct	BoundingBoxXYZ
class	LineRGBD
	High-level class for template matching using the LINEMOD approach based on RGB and Depth data. More...
class	EnergyMaps
	Stores a set of energy maps. More...
class	LinearizedMaps
	Stores a set of linearized maps. More...
struct	LINEMODDetection
	Represents a detection of a template using the LINEMOD approach. More...
class	LINEMOD
	Template matching using the LINEMOD approach. More...
class	MaskMap
struct	GradientXY
	A point structure representing Euclidean xyz coordinates, and the intensity value. More...
class	QuantizableModality
	Interface for a quantizable modality. More...
class	QuantizedMap
struct	RegionXY
	Defines a region in XY-space. More...
struct	QuantizedMultiModFeature
	Feature that defines a position and quantized value in a specific modality. More...
struct	SparseQuantizedMultiModTemplate
	A multi-modality template constructed from a set of quantized multi-modality features. More...
struct	LINEMOD_OrientationMap
	Map that stores orientations. More...
struct	QuantizedNormalLookUpTable
	Look-up-table for fast surface normal quantization. More...
class	SurfaceNormalModality
	Modality based on surface normals. More...
class	SolverDidntConvergeException
	An exception that is thrown when the non linear solver didn't converge. More...
class	NotEnoughPointsException
	An exception that is thrown when the number of correspondents is not equal to the minimum required. More...
class	GeneralizedIterativeClosestPoint
	GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al. More...
class	GeneralizedIterativeClosestPoint6D
	GeneralizedIterativeClosestPoint6D integrates L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm. More...
class	GraphRegistration
	GraphRegistration class is the base class for graph-based registration methods More...
class	SampleConsensusInitialAlignment
	SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al. More...
class	IterativeClosestPoint
	IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm. More...
class	IterativeClosestPointWithNormals
	IterativeClosestPointWithNormals is a special case of IterativeClosestPoint, that uses a transformation estimated based on Point to Plane distances by default. More...
class	IterativeClosestPointNonLinear
	IterativeClosestPointNonLinear is an ICP variant that uses Levenberg-Marquardt optimization backend. More...
class	JointIterativeClosestPoint
	JointIterativeClosestPoint extends ICP to multiple frames which share the same transform. More...
class	NormalDistributionsTransform
	A 3D Normal Distribution Transform registration implementation for point cloud data. More...
class	NormalDistributionsTransform2D
	NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching. More...
class	PairwiseGraphRegistration
	PairwiseGraphRegistration class aligns the clouds two by two More...
class	PPFHashMapSearch
class	PPFRegistration
	Class that registers two point clouds based on their sets of PPFSignatures. More...
class	PyramidFeatureHistogram
	Class that compares two sets of features by using a multiscale representation of the features inside a pyramid. More...
class	Registration
	Registration represents the base registration class for general purpose, ICP-like methods. More...
class	SampleConsensusPrerejective
	Pose estimation and alignment class using a prerejective RANSAC routine. More...
class	LeastMedianSquares
	LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. More...
class	MaximumLikelihoodSampleConsensus
	MaximumLikelihoodSampleConsensus represents an implementation of the MLESAC (Maximum Likelihood Estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
class	MEstimatorSampleConsensus
	MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
class	ProgressiveSampleConsensus
	ProgressiveSampleConsensus represents an implementation of the PROSAC (PROgressive SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O. More...
class	RandomSampleConsensus
	RandomSampleConsensus represents an implementation of the RANSAC (RANdom SAmple Consensus) algorithm, as described in: "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography", Martin A. More...
class	RandomizedMEstimatorSampleConsensus
	RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus). More...
class	RandomizedRandomSampleConsensus
	RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RANdom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O. More...
class	SampleConsensus
	SampleConsensus represents the base class. More...
class	SampleConsensusModel
	SampleConsensusModel represents the base model class. More...
class	SampleConsensusModelFromNormals
	SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation. More...
struct	Functor
	Base functor all the models that need non linear optimization must define their own one and implement operator() (const Eigen::VectorXd& x, Eigen::VectorXd& fvec) or operator() (const Eigen::VectorXf& x, Eigen::VectorXf& fvec) depending on the chosen _Scalar. More...
class	SampleConsensusModelCircle2D
	SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More...
class	SampleConsensusModelCircle3D
	SampleConsensusModelCircle3D defines a model for 3D circle segmentation. More...
class	SampleConsensusModelCone
	SampleConsensusModelCone defines a model for 3D cone segmentation. More...
class	SampleConsensusModelCylinder
	SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More...
class	SampleConsensusModelEllipse3D
	SampleConsensusModelEllipse3D defines a model for 3D ellipse segmentation. More...
class	SampleConsensusModelLine
	SampleConsensusModelLine defines a model for 3D line segmentation. More...
class	SampleConsensusModelNormalParallelPlane
	SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class	SampleConsensusModelNormalPlane
	SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class	SampleConsensusModelNormalSphere
	SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints. More...
class	SampleConsensusModelParallelLine
	SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints. More...
class	SampleConsensusModelParallelPlane
	SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class	SampleConsensusModelPerpendicularPlane
	SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class	SampleConsensusModelPlane
	SampleConsensusModelPlane defines a model for 3D plane segmentation. More...
class	SampleConsensusModelRegistration
	SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection. More...
class	SampleConsensusModelRegistration2D
	SampleConsensusModelRegistration2D defines a model for Point-To-Point registration outlier rejection using distances between 2D pixels. More...
class	SampleConsensusModelSphere
	SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...
class	SampleConsensusModelStick
	SampleConsensusModelStick defines a model for 3D stick segmentation. More...
class	SampleConsensusModelTorus
	SampleConsensusModelTorus defines a model for 3D torus segmentation. More...
class	ApproximateProgressiveMorphologicalFilter
	Implements the Progressive Morphological Filter for segmentation of ground points. More...
class	Comparator
	Comparator is the base class for comparators that compare two points given some function. More...
class	ConditionalEuclideanClustering
	ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition. More...
class	CPCSegmentation
	A segmentation algorithm partitioning a supervoxel graph. More...
class	CrfNormalSegmentation
class	CrfSegmentation
class	EdgeAwarePlaneComparator
	EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	EuclideanClusterComparator
	EuclideanClusterComparator is a comparator used for finding clusters based on euclidean distance. More...
class	EuclideanPlaneCoefficientComparator
	EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	EuclideanClusterExtraction
	EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...
class	LabeledEuclideanClusterExtraction
	LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. More...
class	ExtractPolygonalPrismData
	ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism. More...
class	GrabCut
	Implementation of the GrabCut segmentation in "GrabCut — Interactive Foreground Extraction using Iterated Graph Cuts" by Carsten Rother, Vladimir Kolmogorov and Andrew Blake. More...
class	GroundPlaneComparator
	GroundPlaneComparator is a Comparator for detecting smooth surfaces suitable for driving. More...
class	LCCPSegmentation
	A simple segmentation algorithm partitioning a supervoxel graph into groups of locally convex connected supervoxels separated by concave borders. More...
class	MinCutSegmentation
	This class implements the segmentation algorithm based on minimal cut of the graph. More...
class	OrganizedConnectedComponentSegmentation
	OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function. More...
class	OrganizedMultiPlaneSegmentation
	OrganizedMultiPlaneSegmentation finds all planes present in the input cloud, and outputs a vector of plane equations, as well as a vector of point clouds corresponding to the inliers of each detected plane. More...
class	PlanarPolygonFusion
	PlanarPolygonFusion takes a list of 2D planar polygons and attempts to reduce them to a minimum set that best represents the scene, based on various given comparators. More...
class	PlanarRegion
	PlanarRegion represents a set of points that lie in a plane. More...
class	PlaneCoefficientComparator
	PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	PlaneRefinementComparator
	PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	ProgressiveMorphologicalFilter
	Implements the Progressive Morphological Filter for segmentation of ground points. More...
class	Region3D
	Region3D represents summary statistics of a 3D collection of points. More...
class	RegionGrowing
	Implements the well known Region Growing algorithm used for segmentation. More...
class	RegionGrowingRGB
	Implements the well known Region Growing algorithm used for segmentation based on color of points. More...
class	RGBPlaneCoefficientComparator
	RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	SACSegmentation
	SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation. More...
class	SACSegmentationFromNormals
	SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...
class	SeededHueSegmentation
	SeededHueSegmentation. More...
class	SegmentDifferences
	SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the difference between them for a maximum given distance threshold. More...
class	Supervoxel
	Supervoxel container class - stores a cluster extracted using supervoxel clustering. More...
class	SupervoxelClustering
	Implements a supervoxel algorithm based on voxel structure, normals, and rgb values. More...
class	UnaryClassifier
class	DigitalElevationMapBuilder
	Build a Digital Elevation Map in the column-disparity space from a disparity map and a color image of the scene. More...
class	DisparityMapConverter
	Compute point cloud from the disparity map. More...
class	StereoGrabberBase
	Base class for Stereo file grabber. More...
class	StereoGrabber
class	StereoMatching
	Stereo Matching abstract class. More...
class	GrayStereoMatching
	Stereo Matching abstract class for Grayscale images. More...
class	BlockBasedStereoMatching
	Block based (or fixed window) Stereo Matching class. More...
class	AdaptiveCostSOStereoMatching
	Adaptive Cost 2-pass Scanline Optimization Stereo Matching class. More...
class	BilateralUpsampling
	Bilateral filtering implementation, based on the following paper: More...
class	ConcaveHull
	ConcaveHull (alpha shapes) using libqhull library. More...
class	ConvexHull
	ConvexHull using libqhull library. More...
class	EarClipping
	The ear clipping triangulation algorithm. More...
class	GreedyProjectionTriangulation
	GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More...
class	GridProjection
	Grid projection surface reconstruction method. More...
class	MarchingCubes
	The marching cubes surface reconstruction algorithm. More...
class	MarchingCubesHoppe
	The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et. More...
class	MarchingCubesRBF
	The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions. More...
struct	MLSResult
	Data structure used to store the results of the MLS fitting. More...
class	MovingLeastSquares
	MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
class	OrganizedFastMesh
	Simple triangulation/surface reconstruction for organized point clouds. More...
class	Poisson
	The Poisson surface reconstruction algorithm. More...
class	CloudSurfaceProcessing
	CloudSurfaceProcessing represents the base class for algorithms that takes a point cloud as input and produces a new output cloud that has been modified towards a better surface representation. More...
class	MeshProcessing
	MeshProcessing represents the base class for mesh processing algorithms. More...
class	PCLSurfaceBase
	Pure abstract class. More...
class	SurfaceReconstruction
	SurfaceReconstruction represents a base surface reconstruction class. More...
class	MeshConstruction
	MeshConstruction represents a base surface reconstruction class. More...
class	SurfelSmoothing
class	TextureMapping
	The texture mapping algorithm. More...
class	MeshQuadricDecimationVTK
	PCL mesh decimation based on vtkQuadricDecimation from the VTK library. More...
class	MeshSmoothingLaplacianVTK
	PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library. More...
class	MeshSmoothingWindowedSincVTK
	PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library. More...
class	MeshSubdivisionVTK
	PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library. More...
class	VTKUtils
class	RegistrationVisualizer
	RegistrationVisualizer represents the base class for rendering the intermediate positions occupied by the source point cloud during it's registration to the target point cloud. More...
class	vtkXRenderWindowInteractor

Typedefs
using	BivariatePolynomiald = BivariatePolynomialT< double >
using	BivariatePolynomial = BivariatePolynomialT< float >
using	GlasbeyLUT = ColorLUT< pcl::LUT_GLASBEY >
using	ViridisLUT = ColorLUT< pcl::LUT_VIRIDIS >
using	PolynomialCalculationsd = PolynomialCalculationsT< double >
using	PolynomialCalculations = PolynomialCalculationsT< float >
using	VectorAverage2f = VectorAverage< float, 2 >
using	VectorAverage3f = VectorAverage< float, 3 >
using	VectorAverage4f = VectorAverage< float, 4 >
using	Correspondences = std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > >
using	CorrespondencesPtr = shared_ptr< Correspondences >
using	CorrespondencesConstPtr = shared_ptr< const Correspondences >
using	PointCorrespondences3DVector = std::vector< PointCorrespondence3D, Eigen::aligned_allocator< PointCorrespondence3D > >
using	PointCorrespondences6DVector = std::vector< PointCorrespondence6D, Eigen::aligned_allocator< PointCorrespondence6D > >
using	Vector2fMap = Eigen::Map< Eigen::Vector2f >
using	Vector2fMapConst = const Eigen::Map< const Eigen::Vector2f >
using	Array3fMap = Eigen::Map< Eigen::Array3f >
using	Array3fMapConst = const Eigen::Map< const Eigen::Array3f >
using	Array4fMap = Eigen::Map< Eigen::Array4f, Eigen::Aligned >
using	Array4fMapConst = const Eigen::Map< const Eigen::Array4f, Eigen::Aligned >
using	Vector3fMap = Eigen::Map< Eigen::Vector3f >
using	Vector3fMapConst = const Eigen::Map< const Eigen::Vector3f >
using	Vector4fMap = Eigen::Map< Eigen::Vector4f, Eigen::Aligned >
using	Vector4fMapConst = const Eigen::Map< const Eigen::Vector4f, Eigen::Aligned >
using	Vector3c = Eigen::Matrix< std::uint8_t, 3, 1 >
using	Vector3cMap = Eigen::Map< Vector3c >
using	Vector3cMapConst = const Eigen::Map< const Vector3c >
using	Vector4c = Eigen::Matrix< std::uint8_t, 4, 1 >
using	Vector4cMap = Eigen::Map< Vector4c, Eigen::Aligned >
using	Vector4cMapConst = const Eigen::Map< const Vector4c, Eigen::Aligned >
using	ModelCoefficientsPtr = ModelCoefficients::Ptr
using	ModelCoefficientsConstPtr = ModelCoefficients::ConstPtr
using	IndicesPtr = shared_ptr< Indices >
using	IndicesConstPtr = shared_ptr< const Indices >
using	HeaderPtr = PCLHeader::Ptr
using	HeaderConstPtr = PCLHeader::ConstPtr
using	PCLImagePtr = PCLImage::Ptr
using	PCLImageConstPtr = PCLImage::ConstPtr
using	PCLPointCloud2Ptr = PCLPointCloud2::Ptr
using	PCLPointCloud2ConstPtr = PCLPointCloud2::ConstPtr
using	PCLPointFieldPtr = PCLPointField::Ptr
using	PCLPointFieldConstPtr = PCLPointField::ConstPtr
using	MsgFieldMap = std::vector< detail::FieldMapping >
using	BorderTraits = std::bitset< 32 >
	Data type to store extended information about a transition from foreground to backgroundSpecification of the fields for BorderDescription::traits. More...
using	PointIndicesPtr = PointIndices::Ptr
using	PointIndicesConstPtr = PointIndices::ConstPtr
using	PolygonMeshPtr = PolygonMesh::Ptr
using	PolygonMeshConstPtr = PolygonMesh::ConstPtr
using	TextureMeshPtr = TextureMesh::Ptr
using	TextureMeshConstPtr = TextureMesh::ConstPtr
template<typename ... >
using	void_t = void
template<typename T >
using	remove_cvref_t = std::remove_cv_t< std::remove_reference_t< T > >
using	index_t = detail::int_type_t< detail::index_type_size, detail::index_type_signed >
	Type used for an index in PCL. More...
using	uindex_t = detail::int_type_t< detail::index_type_size, false >
	Type used for an unsigned index in PCL. More...
template<typename Allocator = std::allocator<index_t>>
using	IndicesAllocator = std::vector< index_t, Allocator >
	Type used for indices in PCL. More...
using	Indices = IndicesAllocator<>
	Type used for indices in PCL. More...
template<typename T >
using	AlignedVector = std::vector< T, Eigen::aligned_allocator< T > >
	Type used for aligned vector of Eigen objects in PCL. More...
using	VerticesPtr = Vertices::Ptr
using	VerticesConstPtr = Vertices::ConstPtr
using	Depth2DComparisonFeatureHandler = MultiChannel2DComparisonFeatureHandler< float, 1 >
using	IntensityDepth2DComparisonFeatureHandler = MultiChannel2DComparisonFeatureHandler< float, 2 >
using	RGB2DComparisonFeatureHandler = MultiChannel2DComparisonFeatureHandler< float, 3 >
using	RGBD2DComparisonFeatureHandler = MultiChannel2DComparisonFeatureHandler< float, 4 >
using	ScaledDepth2DComparisonFeatureHandler = ScaledMultiChannel2DComparisonFeatureHandler< float, 1, 0, true >
using	ScaledIntensityDepth2DComparisonFeatureHandler = ScaledMultiChannel2DComparisonFeatureHandler< float, 2, 1, true >
using	ScaledRGBD2DComparisonFeatureHandler = ScaledMultiChannel2DComparisonFeatureHandler< float, 4, 3, true >
using	ScaledDepth2DComparisonFeatureHandlerCCodeGenerator = ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator< float, 1, 0, true >
using	Depth2DDataSet = MultiChannel2DDataSet< float, 1 >
using	IntensityDepth2DDataSet = MultiChannel2DDataSet< float, 2 >
using	RGB2DDataSet = MultiChannel2DDataSet< float, 3 >
using	RGBD2DDataSet = MultiChannel2DDataSet< float, 4 >
using	IndicesClusters = std::vector< pcl::PointIndices >
using	IndicesClustersPtr = shared_ptr< std::vector< pcl::PointIndices > >

Enumerations
enum	ColorLUTName { LUT_GLASBEY , LUT_VIRIDIS }
enum	InterpolationType {   BORDER_CONSTANT = 0 , BORDER_REPLICATE = 1 , BORDER_REFLECT = 2 , BORDER_WRAP = 3 ,   BORDER_REFLECT_101 = 4 , BORDER_TRANSPARENT = 5 , BORDER_DEFAULT = BORDER_REFLECT_101 }
enum	NormType {   L1 , L2_SQR , L2 , LINF ,   JM , B , SUBLINEAR , CS ,   DIV , PF , K , KL ,   HIK }
	Enum that defines all the types of norms available. More...
enum	BorderTrait {   BORDER_TRAIT__OBSTACLE_BORDER , BORDER_TRAIT__SHADOW_BORDER , BORDER_TRAIT__VEIL_POINT , BORDER_TRAIT__SHADOW_BORDER_TOP ,   BORDER_TRAIT__SHADOW_BORDER_RIGHT , BORDER_TRAIT__SHADOW_BORDER_BOTTOM , BORDER_TRAIT__SHADOW_BORDER_LEFT , BORDER_TRAIT__OBSTACLE_BORDER_TOP ,   BORDER_TRAIT__OBSTACLE_BORDER_RIGHT , BORDER_TRAIT__OBSTACLE_BORDER_BOTTOM , BORDER_TRAIT__OBSTACLE_BORDER_LEFT , BORDER_TRAIT__VEIL_POINT_TOP ,   BORDER_TRAIT__VEIL_POINT_RIGHT , BORDER_TRAIT__VEIL_POINT_BOTTOM , BORDER_TRAIT__VEIL_POINT_LEFT }
	Specification of the fields for BorderDescription::traits. More...
enum	HistogramInterpolationMethod { INTERP_NONE , INTERP_TRILINEAR , INTERP_QUADRILINEAR }
	Different histogram interpolation methods. More...
enum	MorphologicalOperators { MORPH_OPEN , MORPH_CLOSE , MORPH_DILATE , MORPH_ERODE }
enum	SacModel {   SACMODEL_PLANE , SACMODEL_LINE , SACMODEL_CIRCLE2D , SACMODEL_CIRCLE3D ,   SACMODEL_SPHERE , SACMODEL_CYLINDER , SACMODEL_CONE , SACMODEL_TORUS ,   SACMODEL_PARALLEL_LINE , SACMODEL_PERPENDICULAR_PLANE , SACMODEL_PARALLEL_LINES , SACMODEL_NORMAL_PLANE ,   SACMODEL_NORMAL_SPHERE , SACMODEL_REGISTRATION , SACMODEL_REGISTRATION_2D , SACMODEL_PARALLEL_PLANE ,   SACMODEL_NORMAL_PARALLEL_PLANE , SACMODEL_STICK , SACMODEL_ELLIPSE3D }

Functions
float	rad2deg (float alpha)
	Convert an angle from radians to degrees. More...
float	deg2rad (float alpha)
	Convert an angle from degrees to radians. More...
double	rad2deg (double alpha)
	Convert an angle from radians to degrees. More...
double	deg2rad (double alpha)
	Convert an angle from degrees to radians. More...
float	normAngle (float alpha)
	Normalize an angle to (-PI, PI]. More...
template<typename real >
std::ostream &	operator<< (std::ostream &os, const BivariatePolynomialT< real > &p)
template<typename PointT , typename Scalar >
unsigned int	compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
template<typename PointT >
unsigned int	compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the 3x3 covariance matrix of a given set of points. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute normalized the 3x3 covariance matrix of a given set of points. More...
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the 3x3 covariance matrix of a given set of points using their indices. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the 3x3 covariance matrix of a given set of points using their indices. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix)
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix)
template<typename PointT , typename Scalar >
unsigned int	computeCentroidAndOBB (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 1 > &centroid, Eigen::Matrix< Scalar, 3, 1 > &obb_center, Eigen::Matrix< Scalar, 3, 1 > &obb_dimensions, Eigen::Matrix< Scalar, 3, 3 > &obb_rotational_matrix)
	Compute centroid, OBB (Oriented Bounding Box), PCA axes of a given set of points. More...
template<typename PointT , typename Scalar >
unsigned int	computeCentroidAndOBB (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 3, 1 > &centroid, Eigen::Matrix< Scalar, 3, 1 > &obb_center, Eigen::Matrix< Scalar, 3, 1 > &obb_dimensions, Eigen::Matrix< Scalar, 3, 3 > &obb_rotational_matrix)
	Compute centroid, OBB (Oriented Bounding Box), PCA axes of a given set of points. More...
template<typename PointT , typename Scalar >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
	Subtract a centroid from a point cloud and return the de-meaned representation. More...
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation. More...
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation. More...
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation. More...
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
template<typename PointT , typename Scalar >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out, int npts=0)
	Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out, int npts=0)
template<typename PointT >
void	demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out, int npts=0)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
template<typename PointT , typename Scalar >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
	Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
template<typename PointT >
void	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
template<typename PointT , typename Scalar >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
	General, all purpose nD centroid estimation for a set of points using their indices. More...
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXf &centroid)
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXd &centroid)
template<typename PointT , typename Scalar >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
	General, all purpose nD centroid estimation for a set of points using their indices. More...
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::VectorXf &centroid)
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::VectorXd &centroid)
template<typename PointT , typename Scalar >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
	General, all purpose nD centroid estimation for a set of points using their indices. More...
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXf &centroid)
template<typename PointT >
void	computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXd &centroid)
template<typename PointInT , typename PointOutT >
std::size_t	computeCentroid (const pcl::PointCloud< PointInT > &cloud, PointOutT &centroid)
	Compute the centroid of a set of points and return it as a point. More...
template<typename PointInT , typename PointOutT >
std::size_t	computeCentroid (const pcl::PointCloud< PointInT > &cloud, const Indices &indices, PointOutT &centroid)
	Compute the centroid of a set of points and return it as a point. More...
PCL_EXPORTS RGB	getRandomColor (double min=0.2, double max=2.8)
template<typename T , std::uint8_t bits = 8>
std::array< T, 1<< bits >	RGB2sRGB_LUT () noexcept
	Returns a Look-Up Table useful in converting RGB to sRGB. More...
template<typename T , std::size_t discretizations = 4000>
const std::array< T, discretizations > &	XYZ2LAB_LUT () noexcept
	Returns a Look-Up Table useful in converting scaled CIE XYZ into CIE L*a*b*. More...
double	getAngle3D (const Eigen::Vector4f &v1, const Eigen::Vector4f &v2, const bool in_degree=false)
	Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
double	getAngle3D (const Eigen::Vector3f &v1, const Eigen::Vector3f &v2, const bool in_degree=false)
	Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
void	getMeanStd (const std::vector< float > &values, double &mean, double &stddev)
	Compute both the mean and the standard deviation of an array of values. More...
template<typename PointT >
void	getPointsInBox (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, Indices &indices)
	Get a set of points residing in a box given its bounds. More...
template<typename PointT >
void	getMaxDistance (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt)
	Get the point at maximum distance from a given point and a given pointcloud. More...
template<typename PointT >
void	getMaxDistance (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt)
	Get the point at maximum distance from a given point and a given pointcloud. More...
template<typename PointT >
void	getMinMax3D (const pcl::PointCloud< PointT > &cloud, PointT &min_pt, PointT &max_pt)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
template<typename PointT >
void	getMinMax3D (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
template<typename PointT >
void	getMinMax3D (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
template<typename PointT >
void	getMinMax3D (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
template<typename PointT >
double	getCircumcircleRadius (const PointT &pa, const PointT &pb, const PointT &pc)
	Compute the radius of a circumscribed circle for a triangle formed of three points pa, pb, and pc. More...
template<typename PointT >
void	getMinMax (const PointT &histogram, int len, float &min_p, float &max_p)
	Get the minimum and maximum values on a point histogram. More...
template<typename PointT >
float	calculatePolygonArea (const pcl::PointCloud< PointT > &polygon)
	Calculate the area of a polygon given a point cloud that defines the polygon. More...
PCL_EXPORTS void	getMinMax (const pcl::PCLPointCloud2 &cloud, int idx, const std::string &field_name, float &min_p, float &max_p)
	Get the minimum and maximum values on a point histogram. More...
PCL_EXPORTS void	getMeanStdDev (const std::vector< float > &values, double &mean, double &stddev)
	Compute both the mean and the standard deviation of an array of values. More...
template<typename IteratorT , typename Functor >
auto	computeMedian (IteratorT begin, IteratorT end, Functor f) noexcept -> std::result_of_t< Functor(decltype(*begin))>
	Compute the median of a list of values (fast). More...
template<typename IteratorT >
auto	computeMedian (IteratorT begin, IteratorT end) noexcept -> typename std::iterator_traits< IteratorT >::value_type
	Compute the median of a list of values (fast). More...
template<typename PointInT , typename PointOutT >
void	copyPoint (const PointInT &point_in, PointOutT &point_out)
	Copy the fields of a source point into a target point. More...
PCL_EXPORTS void	lineToLineSegment (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &pt1_seg, Eigen::Vector4f &pt2_seg)
	Get the shortest 3D segment between two 3D lines. More...
double	sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir)
	Get the square distance from a point to a line (represented by a point and a direction) More...
double	sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir, const double sqr_length)
	Get the square distance from a point to a line (represented by a point and a direction) More...
template<typename PointT >
double	getMaxSegment (const pcl::PointCloud< PointT > &cloud, PointT &pmin, PointT &pmax)
	Obtain the maximum segment in a given set of points, and return the minimum and maximum points. More...
template<typename PointT >
double	getMaxSegment (const pcl::PointCloud< PointT > &cloud, const Indices &indices, PointT &pmin, PointT &pmax)
	Obtain the maximum segment in a given set of points, and return the minimum and maximum points. More...
template<typename PointType1 , typename PointType2 >
float	squaredEuclideanDistance (const PointType1 &p1, const PointType2 &p2)
	Calculate the squared euclidean distance between the two given points. More...
template<>
float	squaredEuclideanDistance (const PointXY &p1, const PointXY &p2)
	Calculate the squared euclidean distance between the two given points. More...
template<typename PointType1 , typename PointType2 >
float	euclideanDistance (const PointType1 &p1, const PointType2 &p2)
	Calculate the euclidean distance between the two given points. More...
template<typename Scalar , typename Roots >
void	computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots)
	Compute the roots of a quadratic polynom x^2 + b*x + c = 0. More...
template<typename Matrix , typename Roots >
void	computeRoots (const Matrix &m, Roots &roots)
	computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues More...
template<typename Matrix , typename Vector >
void	eigen22 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determine the smallest eigenvalue and its corresponding eigenvector More...
template<typename Matrix , typename Vector >
void	eigen22 (const Matrix &mat, Matrix &eigenvectors, Vector &eigenvalues)
	determine the smallest eigenvalue and its corresponding eigenvector More...
template<typename Matrix , typename Vector >
void	computeCorrespondingEigenVector (const Matrix &mat, const typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi definite input matrix More...
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi definite input matrix More...
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, Vector &evals)
	determines the eigenvalues of the symmetric positive semi definite input matrix More...
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals)
	determines the eigenvalues and corresponding eigenvectors of the symmetric positive semi definite input matrix More...
template<typename Matrix >
Matrix::Scalar	invert2x2 (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a 2x2 matrix. More...
template<typename Matrix >
Matrix::Scalar	invert3x3SymMatrix (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a 3x3 symmetric matrix. More...
template<typename Matrix >
Matrix::Scalar	invert3x3Matrix (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a general 3x3 matrix. More...
template<typename Matrix >
Matrix::Scalar	determinant3x3Matrix (const Matrix &matrix)
	Calculate the determinant of a 3x3 matrix. More...
void	getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation)
	Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
Eigen::Affine3f	getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction)
	Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
void	getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation)
	Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
Eigen::Affine3f	getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction)
	Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
void	getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, Eigen::Affine3f &transformation)
	Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
Eigen::Affine3f	getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis)
	Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
void	getTransformationFromTwoUnitVectorsAndOrigin (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, const Eigen::Vector3f &origin, Eigen::Affine3f &transformation)
	Get the transformation that will translate origin to (0,0,0) and rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
template<typename Scalar >
void	getEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &roll, Scalar &pitch, Scalar &yaw)
	Extract the Euler angles (intrinsic rotations, ZYX-convention) from the given transformation. More...
template<typename Scalar >
void	getTranslationAndEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &x, Scalar &y, Scalar &z, Scalar &roll, Scalar &pitch, Scalar &yaw)
	Extract x,y,z and the Euler angles (intrinsic rotations, ZYX-convention) from the given transformation. More...
template<typename Scalar >
void	getTransformation (Scalar x, Scalar y, Scalar z, Scalar roll, Scalar pitch, Scalar yaw, Eigen::Transform< Scalar, 3, Eigen::Affine > &t)
	Create a transformation from the given translation and Euler angles (intrinsic rotations, ZYX-convention) More...
void	getTransformation (float x, float y, float z, float roll, float pitch, float yaw, Eigen::Affine3f &t)
void	getTransformation (double x, double y, double z, double roll, double pitch, double yaw, Eigen::Affine3d &t)
Eigen::Affine3f	getTransformation (float x, float y, float z, float roll, float pitch, float yaw)
	Create a transformation from the given translation and Euler angles (intrinsic rotations, ZYX-convention) More...
template<typename Derived >
void	saveBinary (const Eigen::MatrixBase< Derived > &matrix, std::ostream &file)
	Write a matrix to an output stream. More...
template<typename Derived >
void	loadBinary (Eigen::MatrixBase< Derived > const &matrix, std::istream &file)
	Read a matrix from an input stream. More...
template<typename Derived , typename OtherDerived >
Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type	umeyama (const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false)
	Returns the transformation between two point sets. More...
template<typename Scalar >
void	transformPoint (const Eigen::Matrix< Scalar, 3, 1 > &point_in, Eigen::Matrix< Scalar, 3, 1 > &point_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Transform a point using an affine matrix. More...
template<typename Scalar >
void	transformVector (const Eigen::Matrix< Scalar, 3, 1 > &vector_in, Eigen::Matrix< Scalar, 3, 1 > &vector_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Transform a vector using an affine matrix. More...
template<typename Scalar >
bool	transformLine (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_in, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Transform a line using an affine matrix. More...
template<typename Scalar >
void	transformPlane (const Eigen::Matrix< Scalar, 4, 1 > &plane_in, Eigen::Matrix< Scalar, 4, 1 > &plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Transform plane vectors using an affine matrix. More...
template<typename Scalar >
void	transformPlane (const pcl::ModelCoefficients::ConstPtr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Transform plane vectors using an affine matrix. More...
template<typename Scalar >
bool	checkCoordinateSystem (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_y, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3)
	Check coordinate system integrity. More...
template<typename Scalar >
bool	checkCoordinateSystem (const Eigen::Matrix< Scalar, 3, 1 > &origin, const Eigen::Matrix< Scalar, 3, 1 > &x_direction, const Eigen::Matrix< Scalar, 3, 1 > &y_direction, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3)
	Check coordinate system integrity. More...
template<typename Scalar >
bool	transformBetween2CoordinateSystems (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
	Compute the transformation between two coordinate systems. More...
void	getAllPcdFilesInDirectory (const std::string &directory, std::vector< std::string > &file_names)
	Find all *.pcd files in the directory and return them sorted. More...
std::string	getFilenameWithoutPath (const std::string &input)
	Remove the path from the given string and return only the filename (the remaining string after the last '/') More...
std::string	getFilenameWithoutExtension (const std::string &input)
	Remove the extension from the given string and return only the filename (everything before the last '. More...
std::string	getFileExtension (const std::string &input)
	Get the file extension from the given string (the remaining string after the last '. More...
template<typename PointT , typename Scalar >
unsigned	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
	Compute the 3x3 covariance matrix of a given set of points. More...
bool	lineWithLineIntersection (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4)
	Get the intersection of a two 3D lines in space as a 3D point. More...
bool	lineWithLineIntersection (const pcl::ModelCoefficients &line_a, const pcl::ModelCoefficients &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4)
	Get the intersection of a two 3D lines in space as a 3D point. More...
template<typename Scalar >
bool	planeWithPlaneIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line, double angular_tolerance=0.1)
	Determine the line of intersection of two non-parallel planes using lagrange multipliers. More...
template<typename Scalar >
bool	threePlanesIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, const Eigen::Matrix< Scalar, 4, 1 > &plane_c, Eigen::Matrix< Scalar, 3, 1 > &intersection_point, double determinant_tolerance=1e-6)
	Determine the point of intersection of three non-parallel planes by solving the equations. More...
template<typename PointT >
int	getFieldIndex (const pcl::PointCloud< PointT > &, const std::string &field_name, std::vector< pcl::PCLPointField > &fields)
template<typename PointT >
int	getFieldIndex (const std::string &field_name, std::vector< pcl::PCLPointField > &fields)
	Get the index of a specified field (i.e., dimension/channel) More...
template<typename PointT >
int	getFieldIndex (const std::string &field_name, const std::vector< pcl::PCLPointField > &fields)
	Get the index of a specified field (i.e., dimension/channel) More...
template<typename PointT >
void	getFields (const pcl::PointCloud< PointT > &, std::vector< pcl::PCLPointField > &fields)
template<typename PointT >
void	getFields (std::vector< pcl::PCLPointField > &fields)
template<typename PointT >
std::vector< pcl::PCLPointField >	getFields ()
	Get the list of available fields (i.e., dimension/channel) More...
template<typename PointT >
std::string	getFieldsList (const pcl::PointCloud< PointT > &cloud)
	Get the list of all fields available in a given cloud. More...
template<typename PointInT , typename PointOutT >
void	copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
	Copy all the fields from a given point cloud into a new point cloud. More...
template<typename PointT , typename IndicesVectorAllocator >
void	copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const IndicesAllocator< IndicesVectorAllocator > &indices, pcl::PointCloud< PointT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointInT , typename PointOutT , typename IndicesVectorAllocator >
void	copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const IndicesAllocator< IndicesVectorAllocator > &indices, pcl::PointCloud< PointOutT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointT >
void	copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointInT , typename PointOutT >
void	copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointOutT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointT >
void	copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointInT , typename PointOutT >
void	copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointOutT > &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
template<typename PointIn1T , typename PointIn2T , typename PointOutT >
void	concatenateFields (const pcl::PointCloud< PointIn1T > &cloud1_in, const pcl::PointCloud< PointIn2T > &cloud2_in, pcl::PointCloud< PointOutT > &cloud_out)
	Concatenate two datasets representing different fields. More...
template<typename PointT >
void	copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, int top, int bottom, int left, int right, pcl::InterpolationType border_type, const PointT &value)
	Copy a point cloud inside a larger one interpolating borders. More...
template<typename FloatVectorT >
float	selectNorm (FloatVectorT A, FloatVectorT B, int dim, NormType norm_type)
	Method that calculates any norm type available, based on the norm_type variable. More...
template<typename FloatVectorT >
float	L1_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the L1 norm of the vector between two points. More...
template<typename FloatVectorT >
float	L2_Norm_SQR (FloatVectorT A, FloatVectorT B, int dim)
	Compute the squared L2 norm of the vector between two points. More...
template<typename FloatVectorT >
float	L2_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the L2 norm of the vector between two points. More...
template<typename FloatVectorT >
float	Linf_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the L-infinity norm of the vector between two points. More...
template<typename FloatVectorT >
float	JM_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the JM norm of the vector between two points. More...
template<typename FloatVectorT >
float	B_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the B norm of the vector between two points. More...
template<typename FloatVectorT >
float	Sublinear_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the sublinear norm of the vector between two points. More...
template<typename FloatVectorT >
float	CS_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the CS norm of the vector between two points. More...
template<typename FloatVectorT >
float	Div_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the div norm of the vector between two points. More...
template<typename FloatVectorT >
float	PF_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2)
	Compute the PF norm of the vector between two points. More...
template<typename FloatVectorT >
float	K_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2)
	Compute the K norm of the vector between two points. More...
template<typename FloatVectorT >
float	KL_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the KL between two discrete probability density functions. More...
template<typename FloatVectorT >
float	HIK_Norm (FloatVectorT A, FloatVectorT B, int dim)
	Compute the HIK norm of the vector between two points. More...
template<typename PointT >
double	estimateProjectionMatrix (typename pcl::PointCloud< PointT >::ConstPtr cloud, Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, const Indices &indices={})
	Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]] R = rotation matrix and t = translation vector More...
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Apply a rigid transform defined by a 4x4 matrix. More...
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Apply a rigid transform defined by a 4x4 matrix. More...
void	transformPointCloud (const pcl::PointCloud< pcl::PointXY > &cloud_in, pcl::PointCloud< pcl::PointXY > &cloud_out, const Eigen::Affine2f &transform, bool copy_all_fields=true)
	Apply an affine transform on a pointcloud having points of type PointXY. More...
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true)
	Apply a rigid transform defined by a 3D offset and a quaternion. More...
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT , typename Scalar >
PointT	transformPoint (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
	Transform a point with members x,y,z. More...
template<typename PointT , typename Scalar >
PointT	transformPointWithNormal (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
	Transform a point with members x,y,z,normal_x,normal_y,normal_z. More...
template<typename PointT , typename Scalar >
double	getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
	Calculates the principal (PCA-based) alignment of the point cloud. More...
bool	planeWithPlaneIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, Eigen::VectorXf &line, double angular_tolerance=0.1)
bool	planeWithPlaneIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, Eigen::VectorXd &line, double angular_tolerance=0.1)
bool	threePlanesIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, const Eigen::Vector4f &plane_c, Eigen::Vector3f &intersection_point, double determinant_tolerance=1e-6)
bool	threePlanesIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, const Eigen::Vector4d &plane_c, Eigen::Vector3d &intersection_point, double determinant_tolerance=1e-6)
int	getFieldIndex (const pcl::PCLPointCloud2 &cloud, const std::string &field_name)
	Get the index of a specified field (i.e., dimension/channel) More...
std::string	getFieldsList (const pcl::PCLPointCloud2 &cloud)
	Get the available point cloud fields as a space separated string. More...
int	getFieldSize (const int datatype)
	Obtains the size of a specific field data type in bytes. More...
PCL_EXPORTS void	getFieldsSizes (const std::vector< pcl::PCLPointField > &fields, std::vector< int > &field_sizes)
	Obtain a vector with the sizes of all valid fields (e.g., not "_") More...
int	getFieldType (const int size, char type)
	Obtains the type of the PCLPointField from a specific size and type. More...
char	getFieldType (const int type)
	Obtains the type of the PCLPointField from a specific PCLPointField as a char. More...
PCL_EXPORTS int	interpolatePointIndex (int p, int length, InterpolationType type)
template<typename PointT >
bool	concatenate (const pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2, pcl::PointCloud< PointT > &cloud_out)
	Concatenate two pcl::PointCloud<PointT> More...
bool	concatenate (const pcl::PCLPointCloud2 &cloud1, const pcl::PCLPointCloud2 &cloud2, pcl::PCLPointCloud2 &cloud_out)
	Concatenate two pcl::PCLPointCloud2. More...
bool	concatenate (const pcl::PolygonMesh &mesh1, const pcl::PolygonMesh &mesh2, pcl::PolygonMesh &mesh_out)
	Concatenate two pcl::PolygonMesh. More...
PCL_EXPORTS void	copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const Indices &indices, pcl::PCLPointCloud2 &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
PCL_EXPORTS void	copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const IndicesAllocator< Eigen::aligned_allocator< index_t > > &indices, pcl::PCLPointCloud2 &cloud_out)
	Extract the indices of a given point cloud as a new point cloud. More...
PCL_EXPORTS void	copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, pcl::PCLPointCloud2 &cloud_out)
	Copy fields and point cloud data from cloud_in to cloud_out. More...
template<typename Point1T , typename Point2T >
constexpr bool	isSamePointType () noexcept
	Check if two given point types are the same or not. More...
PCL_EXPORTS bool	concatenateFields (const pcl::PCLPointCloud2 &cloud1_in, const pcl::PCLPointCloud2 &cloud2_in, pcl::PCLPointCloud2 &cloud_out)
	Concatenate two datasets representing different fields. More...
PCL_EXPORTS bool	getPointCloudAsEigen (const pcl::PCLPointCloud2 &in, Eigen::MatrixXf &out)
	Copy the XYZ dimensions of a pcl::PCLPointCloud2 into Eigen format. More...
PCL_EXPORTS bool	getEigenAsPointCloud (Eigen::MatrixXf &in, pcl::PCLPointCloud2 &out)
	Copy the XYZ dimensions from an Eigen MatrixXf into a pcl::PCLPointCloud2 message. More...
template<typename PointT >
bool	isFinite (const PointT &pt)
	Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if finite, false otherwise. More...
template<>
bool	isFinite< pcl::Axis > (const pcl::Axis &)
template<>
bool	isFinite< pcl::BRISKSignature512 > (const pcl::BRISKSignature512 &)
template<>
bool	isFinite< pcl::BorderDescription > (const pcl::BorderDescription &)
template<>
bool	isFinite< pcl::Boundary > (const pcl::Boundary &)
template<>
bool	isFinite< pcl::CPPFSignature > (const pcl::CPPFSignature &)
template<>
bool	isFinite< pcl::ESFSignature640 > (const pcl::ESFSignature640 &)
template<>
bool	isFinite< pcl::FPFHSignature33 > (const pcl::FPFHSignature33 &)
template<>
bool	isFinite< pcl::GASDSignature512 > (const pcl::GASDSignature512 &)
template<>
bool	isFinite< pcl::GASDSignature984 > (const pcl::GASDSignature984 &)
template<>
bool	isFinite< pcl::GASDSignature7992 > (const pcl::GASDSignature7992 &)
template<>
bool	isFinite< pcl::GRSDSignature21 > (const pcl::GRSDSignature21 &)
template<>
bool	isFinite< pcl::Intensity > (const pcl::Intensity &)
template<>
bool	isFinite< pcl::IntensityGradient > (const pcl::IntensityGradient &)
template<>
bool	isFinite< pcl::Label > (const pcl::Label &)
template<>
bool	isFinite< pcl::MomentInvariants > (const pcl::MomentInvariants &)
template<>
bool	isFinite< pcl::NormalBasedSignature12 > (const pcl::NormalBasedSignature12 &)
template<>
bool	isFinite< pcl::PFHRGBSignature250 > (const pcl::PFHRGBSignature250 &)
template<>
bool	isFinite< pcl::PFHSignature125 > (const pcl::PFHSignature125 &)
template<>
bool	isFinite< pcl::PPFRGBSignature > (const pcl::PPFRGBSignature &)
template<>
bool	isFinite< pcl::PPFSignature > (const pcl::PPFSignature &pt)
template<>
bool	isFinite< pcl::PrincipalCurvatures > (const pcl::PrincipalCurvatures &)
template<>
bool	isFinite< pcl::PrincipalRadiiRSD > (const pcl::PrincipalRadiiRSD &)
template<>
bool	isFinite< pcl::RGB > (const pcl::RGB &)
template<>
bool	isFinite< pcl::ReferenceFrame > (const pcl::ReferenceFrame &)
template<>
bool	isFinite< pcl::SHOT1344 > (const pcl::SHOT1344 &)
template<>
bool	isFinite< pcl::SHOT352 > (const pcl::SHOT352 &)
template<>
bool	isFinite< pcl::ShapeContext1980 > (const pcl::ShapeContext1980 &)
template<>
bool	isFinite< pcl::UniqueShapeContext1960 > (const pcl::UniqueShapeContext1960 &)
template<>
bool	isFinite< pcl::VFHSignature308 > (const pcl::VFHSignature308 &)
template<>
bool	isFinite< pcl::PointXY > (const pcl::PointXY &p)
template<>
bool	isFinite< pcl::Normal > (const pcl::Normal &n)
template<typename PointT , traits::HasNoXY< PointT > = true>
constexpr bool	isXYFinite (const PointT &) noexcept
template<typename PointT , traits::HasNoXYZ< PointT > = true>
constexpr bool	isXYZFinite (const PointT &) noexcept
template<typename PointT , traits::HasNoNormal< PointT > = true>
constexpr bool	isNormalFinite (const PointT &) noexcept
template<typename PointT , traits::HasXY< PointT > = true>
bool	isXYFinite (const PointT &pt) noexcept
template<typename PointT , traits::HasXYZ< PointT > = true>
bool	isXYZFinite (const PointT &pt) noexcept
template<typename PointT , traits::HasNormal< PointT > = true>
bool	isNormalFinite (const PointT &pt) noexcept
PCL_EXPORTS void	getCameraMatrixFromProjectionMatrix (const Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, Eigen::Matrix3f &camera_matrix)
	Determines the camera matrix from the given projection matrix. More...
double	getTime ()
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Apply an affine transform defined by an Eigen Transform. More...
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Apply an affine transform defined by an Eigen Transform. More...
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Apply an affine transform defined by an Eigen Transform. More...
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Apply a rigid transform defined by a 4x4 matrix. More...
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT , typename Scalar >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
	Transform a point cloud and rotate its normals using an Eigen transform. More...
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true)
template<typename PointT >
void	transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true)
template<typename PointT >
PointT	transformPoint (const PointT &point, const Eigen::Affine3f &transform)
template<typename PointT >
PointT	transformPointWithNormal (const PointT &point, const Eigen::Affine3f &transform)
template<typename PointT >
double	getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Affine3f &transform)
template<typename PointT >
void	createMapping (const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
template<typename PointT >
void	fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map, const std::uint8_t *msg_data)
	Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map. More...
template<typename PointT >
void	fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
	Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map. More...
template<typename PointT >
void	fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud)
	Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object. More...
template<typename PointT >
void	toPCLPointCloud2 (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg, bool padding)
	Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob. More...
template<typename PointT >
void	toPCLPointCloud2 (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
	Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob. More...
template<typename CloudT >
void	toPCLPointCloud2 (const CloudT &cloud, pcl::PCLImage &msg)
	Copy the RGB fields of a PointCloud into pcl::PCLImage format. More...
void	toPCLPointCloud2 (const pcl::PCLPointCloud2 &cloud, pcl::PCLImage &msg)
	Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format. More...
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Correspondence &c)
	overloaded << operator More...
void	getRejectedQueryIndices (const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, Indices &indices, bool presorting_required=true)
	Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection. More...
bool	isBetterCorrespondence (const Correspondence &pc1, const Correspondence &pc2)
	Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort (begin(), end(), isBetterCorrespondence);. More...
template<typename Sequence , typename F >
void	for_each_type (F f)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZ &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const RGB &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Intensity &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Intensity8u &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Intensity32u &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZI &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZL &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Label &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZRGBA &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZRGB &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZRGBL &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZLAB &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZHSV &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXY &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointUV &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const InterestPoint &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Normal &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Axis &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointNormal &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZRGBNormal &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZINormal &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointXYZLNormal &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointWithRange &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointWithViewpoint &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const MomentInvariants &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PrincipalRadiiRSD &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Boundary &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PrincipalCurvatures &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PFHSignature125 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PFHRGBSignature250 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PPFSignature &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const CPPFSignature &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PPFRGBSignature &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const NormalBasedSignature12 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const ShapeContext1980 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const UniqueShapeContext1960 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const SHOT352 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const SHOT1344 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const ReferenceFrame &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const FPFHSignature33 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const VFHSignature308 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const GRSDSignature21 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const BRISKSignature512 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const ESFSignature640 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const GASDSignature512 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const GASDSignature984 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const GASDSignature7992 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const GFPFHSignature16 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const Narf36 &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const BorderDescription &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const IntensityGradient &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointWithScale &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointSurfel &p)
PCL_EXPORTS std::ostream &	operator<< (std::ostream &os, const PointDEM &p)
template<int N>
std::ostream &	operator<< (std::ostream &os, const Histogram< N > &p)
template<typename T , typename ... Args>
shared_ptr< T >	make_shared (Args &&... args)
	Returns a pcl::shared_ptr compliant with type T's allocation policy. More...
std::ostream &	operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v)
void *	aligned_malloc (std::size_t size)
void	aligned_free (void *ptr)
std::ostream &	operator<< (std::ostream &out, const PCLHeader &h)
bool	operator== (const PCLHeader &lhs, const PCLHeader &rhs)
std::ostream &	operator<< (std::ostream &s, const ::pcl::PCLImage &v)
std::ostream &	operator<< (std::ostream &s, const ::pcl::PCLPointCloud2 &v)
std::ostream &	operator<< (std::ostream &s, const ::pcl::PCLPointField &v)
template<typename PointT >
std::ostream &	operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p)
void	PointXYZRGBtoXYZI (const PointXYZRGB &in, PointXYZI &out)
	Convert a XYZRGB point type to a XYZI. More...
void	PointRGBtoI (const RGB &in, Intensity &out)
	Convert a RGB point type to a I. More...
void	PointRGBtoI (const RGB &in, Intensity8u &out)
	Convert a RGB point type to a I. More...
void	PointRGBtoI (const RGB &in, Intensity32u &out)
	Convert a RGB point type to a I. More...
void	PointXYZRGBtoXYZHSV (const PointXYZRGB &in, PointXYZHSV &out)
	Convert a XYZRGB point type to a XYZHSV. More...
template<typename PointT , traits::HasColor< PointT > = true>
void	PointXYZRGBtoXYZLAB (const PointT &in, PointXYZLAB &out)
	Convert a XYZRGB-based point type to a XYZLAB. More...
void	PointXYZRGBAtoXYZHSV (const PointXYZRGBA &in, PointXYZHSV &out)
	Convert a XYZRGBA point type to a XYZHSV. More...
void	PointXYZHSVtoXYZRGB (const PointXYZHSV &in, PointXYZRGB &out)
void	PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity > &out)
	Convert a RGB point cloud to an Intensity. More...
void	PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity8u > &out)
	Convert a RGB point cloud to an Intensity. More...
void	PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity32u > &out)
	Convert a RGB point cloud to an Intensity. More...
void	PointCloudXYZRGBtoXYZHSV (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZHSV > &out)
	Convert a XYZRGB point cloud to a XYZHSV. More...
void	PointCloudXYZHSVtoXYZRGB (const PointCloud< PointXYZHSV > &in, PointCloud< PointXYZRGB > &out)
	Convert a XYZHSV point cloud to a XYZRGB. More...
void	PointCloudXYZRGBAtoXYZHSV (const PointCloud< PointXYZRGBA > &in, PointCloud< PointXYZHSV > &out)
	Convert a XYZRGB point cloud to a XYZHSV. More...
void	PointCloudXYZRGBtoXYZI (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZI > &out)
	Convert a XYZRGB point cloud to a XYZI. More...
void	PointCloudDepthAndRGBtoXYZRGBA (const PointCloud< Intensity > &depth, const PointCloud< RGB > &image, const float &focal, PointCloud< PointXYZRGBA > &out)
	Convert registered Depth image and RGB image to PointCloudXYZRGBA. More...
std::ostream &	operator<< (std::ostream &s, const ::pcl::PointIndices &v)
std::ostream &	operator<< (std::ostream &s, const ::pcl::PolygonMesh &v)
std::ostream &	operator<< (std::ostream &os, const RangeImage &r)
	/ingroup range_image More...
template<typename PointT , typename ValT >
void	setFieldValue (PointT &pt, std::size_t field_offset, const ValT &value)
	Set the value at a specified field in a point. More...
template<typename PointT , typename ValT >
void	getFieldValue (const PointT &pt, std::size_t field_offset, ValT &value)
	Get the value at a specified field in a point. More...
std::ostream &	operator<< (std::ostream &s, const ::pcl::Vertices &v)
PCL_EXPORTS bool	computeCPPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &c1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &c2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7, float &f8, float &f9, float &f10)
void	solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, const Eigen::Vector4f &point, Eigen::Vector4f &plane_parameters, float &curvature)
	Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. More...
void	solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, float &nx, float &ny, float &nz, float &curvature)
	Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. More...
std::ostream &	operator<< (std::ostream &os, const RangeImageBorderExtractor::Parameters &p)
template<typename PointT >
bool	computePointNormal (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &plane_parameters, float &curvature)
	Compute the Least-Squares plane fit for a given set of points, and return the estimated plane parameters together with the surface curvature. More...
template<typename PointT >
bool	computePointNormal (const pcl::PointCloud< PointT > &cloud, const pcl::Indices &indices, Eigen::Vector4f &plane_parameters, float &curvature)
	Compute the Least-Squares plane fit for a given set of points, using their indices, and return the estimated plane parameters together with the surface curvature. More...
template<typename PointT , typename Scalar >
void	flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 4, 1 > &normal)
	Flip (in place) the estimated normal of a point towards a given viewpoint. More...
template<typename PointT , typename Scalar >
void	flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 3, 1 > &normal)
	Flip (in place) the estimated normal of a point towards a given viewpoint. More...
template<typename PointT >
void	flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, float &nx, float &ny, float &nz)
	Flip (in place) the estimated normal of a point towards a given viewpoint. More...
template<typename PointNT >
bool	flipNormalTowardsNormalsMean (pcl::PointCloud< PointNT > const &normal_cloud, pcl::Indices const &normal_indices, Eigen::Vector3f &normal)
	Flip (in place) normal to get the same sign of the mean of the normals specified by normal_indices. More...
PCL_EXPORTS bool	computePairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
	Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals. More...
PCL_EXPORTS bool	computeRGBPairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &colors1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &colors2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
PCL_EXPORTS bool	computePPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
template<int N>
void	getFeaturePointCloud (const std::vector< Eigen::MatrixXf, Eigen::aligned_allocator< Eigen::MatrixXf > > &histograms2D, PointCloud< Histogram< N > > &histogramsPC)
	Transform a list of 2D matrices into a point cloud containing the values in a vector (Histogram<N>). More...
template<typename PointInT , typename PointNT , typename PointOutT >
Eigen::MatrixXf	computeRSD (const pcl::PointCloud< PointInT > &surface, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
	Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
template<typename PointNT , typename PointOutT >
Eigen::MatrixXf	computeRSD (const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, const std::vector< float > &sqr_dists, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
	Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
template<typename PointT >
void	removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index)
	Removes points with x, y, or z equal to NaN. More...
template<typename PointT >
void	removeNaNNormalsFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index)
	Removes points that have their normals invalid (i.e., equal to NaN) More...
template<typename PointT >
void	removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, Indices &index)
	Removes points with x, y, or z equal to NaN (dry run). More...
template<typename PointT >
void	applyMorphologicalOperator (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, float resolution, const int morphological_operator, pcl::PointCloud< PointT > &cloud_out)
	Apply morphological operator to the z dimension of the input point cloud. More...
template<typename PointT >
PCL_EXPORTS void	applyMorphologicalOperator (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, float resolution, const int morphological_operator, pcl::PointCloud< PointT > &cloud_out)
	Apply morphological operator to the z dimension of the input point cloud. More...
template<typename NormalT >
std::vector< float >	assignNormalWeights (const PointCloud< NormalT > &cloud, index_t index, const Indices &k_indices, const std::vector< float > &k_sqr_distances)
	Assign weights of nearby normals used for refinement. More...
template<typename NormalT >
bool	refineNormal (const PointCloud< NormalT > &cloud, int index, const Indices &k_indices, const std::vector< float > &k_sqr_distances, NormalT &point)
	Refine an indexed point based on its neighbors, this function only writes to the normal_* fields. More...
PCL_EXPORTS void	getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
	Obtain the maximum and minimum points in 3D from a given point cloud. More...
PCL_EXPORTS void	getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, const Indices &indices, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
	Obtain the maximum and minimum points in 3D from a given point cloud. More...
PCL_EXPORTS void	getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
	Obtain the maximum and minimum points in 3D from a given point cloud. More...
PCL_EXPORTS void	getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, const Indices &indices, int x_idx, int y_idx, int z_idx, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
	Obtain the maximum and minimum points in 3D from a given point cloud. More...
Eigen::MatrixXi	getHalfNeighborCellIndices ()
	Get the relative cell indices of the "upper half" 13 neighbors. More...
Eigen::MatrixXi	getAllNeighborCellIndices ()
	Get the relative cell indices of all the 26 neighbors. More...
template<typename PointT >
void	getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. More...
template<typename PointT >
void	getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const Indices &indices, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
	Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. More...
template<typename PointT >
void	approximatePolygon (const PlanarPolygon< PointT > &polygon, PlanarPolygon< PointT > &approx_polygon, float threshold, bool refine=false, bool closed=true)
	see approximatePolygon2D More...
template<typename PointT >
void	approximatePolygon2D (const typename PointCloud< PointT >::VectorType &polygon, typename PointCloud< PointT >::VectorType &approx_polygon, float threshold, bool refine=false, bool closed=true)
	returns an approximate polygon to given 2D contour. More...
template<typename Type >
std::enable_if_t< std::is_floating_point< Type >::value >	copyValueString (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
	inserts a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream. More...
template<typename Type >
std::enable_if_t< std::is_integral< Type >::value >	copyValueString (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
template<>
void	copyValueString< std::int8_t > (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
template<>
void	copyValueString< std::uint8_t > (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
template<typename Type >
std::enable_if_t< std::is_floating_point< Type >::value, bool >	isValueFinite (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count)
	Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not. More...
template<typename Type >
std::enable_if_t< std::is_integral< Type >::value, bool >	isValueFinite (const pcl::PCLPointCloud2 &, const pcl::index_t, const int, const unsigned int, const unsigned int)
template<typename Type >
void	copyStringValue (const std::string &st, pcl::PCLPointCloud2 &cloud, pcl::index_t point_index, unsigned int field_idx, unsigned int fields_count)
	Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string. More...
template<typename Type >
void	copyStringValue (const std::string &st, pcl::PCLPointCloud2 &cloud, pcl::index_t point_index, unsigned int field_idx, unsigned int fields_count, std::istringstream &is)
	Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string. More...
PCL_EXPORTS unsigned int	lzfCompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
	Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm. More...
PCL_EXPORTS unsigned int	lzfDecompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
	Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len. More...
template<typename SequenceSequenceT >
void	split (SequenceSequenceT &result, std::string const &in, const char *const delimiters)
	Lightweight tokenization function This function can be used as a boost::split substitute. More...
PCL_EXPORTS std::string	getTimestamp (const std::chrono::time_point< std::chrono::system_clock > &time=std::chrono::system_clock::now())
	Returns a timestamp in local time as string formatted like boosts to_iso_string see https://www.boost.org/doc/libs/1_81_0/doc/html/date_time/posix_time.html#ptime_to_string Example: 19750101T235959.123456. More...
PCL_EXPORTS std::chrono::time_point< std::chrono::system_clock >	parseTimestamp (std::string timestamp)
	Parses a iso timestring (see https://www.boost.org/doc/libs/1_81_0/doc/html/date_time/posix_time.html#ptime_to_string) and returns a timepoint. More...
template<class FlannIndex , class Query , class Indices , class Distances , class SearchParams >
int	knn_search (const FlannIndex &index, const Query &query, Indices &indices, Distances &dists, unsigned int k, const SearchParams &params)
	Compatibility template function to allow use of various types of indices with FLANN. More...
template<class FlannIndex , class Query , class Indices , class Distances , class SearchParams >
int	radius_search (const FlannIndex &index, const Query &query, Indices &indices, Distances &dists, float radius, const SearchParams &params)
	Compatibility template function to allow use of various types of indices with FLANN. More...
template<typename PointT >
void	getApproximateIndices (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, const typename pcl::PointCloud< PointT >::ConstPtr &cloud_ref, Indices &indices)
	Get a set of approximate indices for a given point cloud into a reference point cloud. More...
template<typename Point1T , typename Point2T >
void	getApproximateIndices (const typename pcl::PointCloud< Point1T >::ConstPtr &cloud_in, const typename pcl::PointCloud< Point2T >::ConstPtr &cloud_ref, Indices &indices)
	Get a set of approximate indices for a given point cloud into a reference point cloud. More...
std::ostream &	operator<< (std::ostream &os, const NarfKeypoint::Parameters &p)
std::ostream &	operator<< (std::ostream &os, const GradientXY &p)
template<class Type >
void	read (std::istream &stream, Type &value)
	Function for reading data from a stream. More...
template<class Type >
void	read (std::istream &stream, Type *value, int nr_values)
	Function for reading data arrays from a stream. More...
template<class Type >
void	write (std::ostream &stream, Type value)
	Function for writing data to a stream. More...
template<class Type >
void	write (std::ostream &stream, Type *value, int nr_values)
	Function for writing data arrays to a stream. More...
template<typename PointT >
float	getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, float max_dist, int nr_threads=1)
	Compute the mean point density of a given point cloud. More...
template<typename PointT >
float	getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const pcl::Indices &indices, float max_dist, int nr_threads=1)
	Compute the mean point density of a given point cloud. More...
template<typename Point >
void	projectPoint (const Point &p, const Eigen::Vector4f &model_coefficients, Point &q)
	Project a point on a planar model given by a set of normalized coefficients. More...
template<typename Point >
double	pointToPlaneDistanceSigned (const Point &p, double a, double b, double c, double d)
	Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. More...
template<typename Point >
double	pointToPlaneDistanceSigned (const Point &p, const Eigen::Vector4f &plane_coefficients)
	Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. More...
template<typename Point >
double	pointToPlaneDistance (const Point &p, double a, double b, double c, double d)
	Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. More...
template<typename Point >
double	pointToPlaneDistance (const Point &p, const Eigen::Vector4f &plane_coefficients)
	Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. More...
template<typename PointT >
void	extractEuclideanClusters (const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the Euclidean distance between points. More...
template<typename PointT >
void	extractEuclideanClusters (const PointCloud< PointT > &cloud, const Indices &indices, const typename search::Search< PointT >::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the Euclidean distance between points. More...
template<typename PointT , typename Normal >
void	extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, float tolerance, const typename KdTree< PointT >::Ptr &tree, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation between points. More...
template<typename PointT , typename Normal >
void	extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, const Indices &indices, const typename KdTree< PointT >::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation between points. More...
bool	comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
	Sort clusters method (for std::sort). More...
template<typename PointT >
void	extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &tree, float tolerance, std::vector< std::vector< PointIndices >> &labeled_clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=std::numeric_limits< unsigned int >::max())
	Decompose a region of space into clusters based on the Euclidean distance between points. More...
bool	compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
	Sort clusters method (for std::sort). More...
template<typename PointT >
bool	isPointIn2DPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon)
	General purpose method for checking if a 3D point is inside or outside a given 2D polygon. More...
template<typename PointT >
bool	isXYPointIn2DXYPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon)
	Check if a 2d point (X and Y coordinates considered only!) is inside or outside a given polygon. More...
template<>
float	squaredEuclideanDistance (const pcl::segmentation::grabcut::Color &c1, const pcl::segmentation::grabcut::Color &c2)
bool	comparePair (std::pair< float, int > i, std::pair< float, int > j)
	This function is used as a comparator for sorting. More...
void	seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGB >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)
	Decompose a region of space into clusters based on the Euclidean distance between points. More...
void	seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGBL >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)
	Decompose a region of space into clusters based on the Euclidean distance between points. More...
template<typename PointT >
void	getPointCloudDifference (const pcl::PointCloud< PointT > &src, double threshold, const typename pcl::search::Search< PointT >::Ptr &tree, pcl::PointCloud< PointT > &output)
	Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold. More...
template<class T >
short int	doStereoRatioFilter (const T *const acc, short int dbest, T sad_min, int ratio_filter, int maxdisp, int precision=100)
template<class T >
short int	doStereoPeakFilter (const T *const acc, short int dbest, int peak_filter, int maxdisp)
bool	comparePoints2D (const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2)
	Sort 2D points in a vector structure. More...
bool	isVisible (const Eigen::Vector2f &X, const Eigen::Vector2f &S1, const Eigen::Vector2f &S2, const Eigen::Vector2f &R=Eigen::Vector2f::Zero())
	Returns if a point X is visible from point R (or the origin) when taking into account the segment between the points S1 and S2. More...

Variables
static constexpr index_t	UNAVAILABLE = static_cast<index_t>(-1)
template<typename F , typename... Args>
constexpr bool	is_invocable_v
template<typename R , typename F , typename... Args>
constexpr bool	is_invocable_r_v
constexpr int	SAC_RANSAC = 0
constexpr int	SAC_LMEDS = 1
constexpr int	SAC_MSAC = 2
constexpr int	SAC_RRANSAC = 3
constexpr int	SAC_RMSAC = 4
constexpr int	SAC_MLESAC = 5
constexpr int	SAC_PROSAC = 6
const int	I_SHIFT_EP [12][2]
	The 12 edges of a cell. More...
const int	I_SHIFT_PT [4]
const int	I_SHIFT_EDGE [3][2]
const unsigned int	edgeTable [256]
const int	triTable [256][16]

Typedef Documentation

AlignedVector

template<typename T >

using pcl::AlignedVector = typedef std::vector<T, Eigen::aligned_allocator<T> >

Type used for aligned vector of Eigen objects in PCL.

Definition at line 139 of file types.h.

Array3fMap

using pcl::Array3fMap = typedef Eigen::Map<Eigen::Array3f>

Definition at line 195 of file point_types.hpp.

Array3fMapConst

using pcl::Array3fMapConst = typedef const Eigen::Map<const Eigen::Array3f>

Definition at line 196 of file point_types.hpp.

Array4fMap

using pcl::Array4fMap = typedef Eigen::Map<Eigen::Array4f, Eigen::Aligned>

Definition at line 197 of file point_types.hpp.

Array4fMapConst

using pcl::Array4fMapConst = typedef const Eigen::Map<const Eigen::Array4f, Eigen::Aligned>

Definition at line 198 of file point_types.hpp.

BivariatePolynomial

using pcl::BivariatePolynomial = typedef BivariatePolynomialT<float>

Definition at line 139 of file bivariate_polynomial.h.

BivariatePolynomiald

using pcl::BivariatePolynomiald = typedef BivariatePolynomialT<double>

Definition at line 138 of file bivariate_polynomial.h.

Correspondences

using pcl::Correspondences = typedef std::vector< pcl::Correspondence, Eigen::aligned_allocator<pcl::Correspondence> >

Definition at line 89 of file correspondence.h.

CorrespondencesConstPtr

using pcl::CorrespondencesConstPtr = typedef shared_ptr<const Correspondences >

Definition at line 91 of file correspondence.h.

CorrespondencesPtr

using pcl::CorrespondencesPtr = typedef shared_ptr<Correspondences>

Definition at line 90 of file correspondence.h.

Depth2DComparisonFeatureHandler

using pcl::Depth2DComparisonFeatureHandler = typedef MultiChannel2DComparisonFeatureHandler<float, 1>

Definition at line 437 of file multi_channel_2d_comparison_feature_handler.h.

Depth2DDataSet

using pcl::Depth2DDataSet = typedef MultiChannel2DDataSet<float, 1>

Definition at line 239 of file multi_channel_2d_data_set.h.

GlasbeyLUT

using pcl::GlasbeyLUT = typedef ColorLUT<pcl::LUT_GLASBEY>

Definition at line 86 of file colors.h.

HeaderConstPtr

using pcl::HeaderConstPtr = typedef PCLHeader::ConstPtr

Definition at line 27 of file PCLHeader.h.

HeaderPtr

using pcl::HeaderPtr = typedef PCLHeader::Ptr

Definition at line 26 of file PCLHeader.h.

index_t

using pcl::index_t = typedef detail::int_type_t<detail::index_type_size, detail::index_type_signed>

Type used for an index in PCL.

Default index_t = int for PCL 1.11, std::int32_t for PCL >= 1.12

Definition at line 112 of file types.h.

Indices

using pcl::Indices = typedef IndicesAllocator<>

Type used for indices in PCL.

Definition at line 133 of file types.h.

IndicesAllocator

template<typename Allocator = std::allocator<index_t>>

using pcl::IndicesAllocator = typedef std::vector<index_t, Allocator>

Type used for indices in PCL.

Todo:

Remove with C++20

Definition at line 128 of file types.h.

IndicesClusters

using pcl::IndicesClusters = typedef std::vector<pcl::PointIndices>

Definition at line 50 of file conditional_euclidean_clustering.h.

IndicesClustersPtr

using pcl::IndicesClustersPtr = typedef shared_ptr<std::vector<pcl::PointIndices> >

Definition at line 51 of file conditional_euclidean_clustering.h.

IndicesConstPtr

using pcl::IndicesConstPtr = typedef shared_ptr<const Indices>

Definition at line 59 of file pcl_base.h.

IndicesPtr

using pcl::IndicesPtr = typedef shared_ptr<Indices>

Definition at line 58 of file pcl_base.h.

IntensityDepth2DComparisonFeatureHandler

using pcl::IntensityDepth2DComparisonFeatureHandler = typedef MultiChannel2DComparisonFeatureHandler<float, 2>

Definition at line 439 of file multi_channel_2d_comparison_feature_handler.h.

IntensityDepth2DDataSet

using pcl::IntensityDepth2DDataSet = typedef MultiChannel2DDataSet<float, 2>

Definition at line 240 of file multi_channel_2d_data_set.h.

ModelCoefficientsConstPtr

using pcl::ModelCoefficientsConstPtr = typedef ModelCoefficients::ConstPtr

Definition at line 25 of file ModelCoefficients.h.

ModelCoefficientsPtr

using pcl::ModelCoefficientsPtr = typedef ModelCoefficients::Ptr

Definition at line 24 of file ModelCoefficients.h.

MsgFieldMap

using pcl::MsgFieldMap = typedef std::vector<detail::FieldMapping>

Definition at line 72 of file point_cloud.h.

PCLImageConstPtr

using pcl::PCLImageConstPtr = typedef PCLImage::ConstPtr

Definition at line 30 of file PCLImage.h.

PCLImagePtr

using pcl::PCLImagePtr = typedef PCLImage::Ptr

Definition at line 29 of file PCLImage.h.

PCLPointCloud2ConstPtr

using pcl::PCLPointCloud2ConstPtr = typedef PCLPointCloud2::ConstPtr

Definition at line 119 of file PCLPointCloud2.h.

PCLPointCloud2Ptr

using pcl::PCLPointCloud2Ptr = typedef PCLPointCloud2::Ptr

Definition at line 118 of file PCLPointCloud2.h.

PCLPointFieldConstPtr

using pcl::PCLPointFieldConstPtr = typedef PCLPointField::ConstPtr

Definition at line 38 of file PCLPointField.h.

PCLPointFieldPtr

using pcl::PCLPointFieldPtr = typedef PCLPointField::Ptr

Definition at line 37 of file PCLPointField.h.

PointCorrespondences3DVector

using pcl::PointCorrespondences3DVector = typedef std::vector<PointCorrespondence3D, Eigen::aligned_allocator<PointCorrespondence3D> >

Definition at line 124 of file correspondence.h.

PointCorrespondences6DVector

using pcl::PointCorrespondences6DVector = typedef std::vector<PointCorrespondence6D, Eigen::aligned_allocator<PointCorrespondence6D> >

Definition at line 138 of file correspondence.h.

PointIndicesConstPtr

using pcl::PointIndicesConstPtr = typedef PointIndices::ConstPtr

Definition at line 24 of file PointIndices.h.

PointIndicesPtr

using pcl::PointIndicesPtr = typedef PointIndices::Ptr

Definition at line 23 of file PointIndices.h.

PolygonMeshConstPtr

using pcl::PolygonMeshConstPtr = typedef PolygonMesh::ConstPtr

Definition at line 101 of file PolygonMesh.h.

PolygonMeshPtr

using pcl::PolygonMeshPtr = typedef PolygonMesh::Ptr

Definition at line 100 of file PolygonMesh.h.

PolynomialCalculations

using pcl::PolynomialCalculations = typedef PolynomialCalculationsT<float>

Definition at line 124 of file polynomial_calculations.h.

PolynomialCalculationsd

using pcl::PolynomialCalculationsd = typedef PolynomialCalculationsT<double>

Definition at line 123 of file polynomial_calculations.h.

remove_cvref_t

template<typename T >

using pcl::remove_cvref_t = typedef std::remove_cv_t<std::remove_reference_t<T> >

Todo:

: Remove in C++17

Definition at line 298 of file type_traits.h.

RGB2DComparisonFeatureHandler

using pcl::RGB2DComparisonFeatureHandler = typedef MultiChannel2DComparisonFeatureHandler<float, 3>

Definition at line 441 of file multi_channel_2d_comparison_feature_handler.h.

RGB2DDataSet

using pcl::RGB2DDataSet = typedef MultiChannel2DDataSet<float, 3>

Definition at line 241 of file multi_channel_2d_data_set.h.

RGBD2DComparisonFeatureHandler

using pcl::RGBD2DComparisonFeatureHandler = typedef MultiChannel2DComparisonFeatureHandler<float, 4>

Definition at line 442 of file multi_channel_2d_comparison_feature_handler.h.

RGBD2DDataSet

using pcl::RGBD2DDataSet = typedef MultiChannel2DDataSet<float, 4>

Definition at line 242 of file multi_channel_2d_data_set.h.

ScaledDepth2DComparisonFeatureHandler

using pcl::ScaledDepth2DComparisonFeatureHandler = typedef ScaledMultiChannel2DComparisonFeatureHandler<float, 1, 0, true>

Definition at line 444 of file multi_channel_2d_comparison_feature_handler.h.

ScaledDepth2DComparisonFeatureHandlerCCodeGenerator

using pcl::ScaledDepth2DComparisonFeatureHandlerCCodeGenerator = typedef ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator<float, 1, 0, true>

Definition at line 451 of file multi_channel_2d_comparison_feature_handler.h.

ScaledIntensityDepth2DComparisonFeatureHandler

using pcl::ScaledIntensityDepth2DComparisonFeatureHandler = typedef ScaledMultiChannel2DComparisonFeatureHandler<float, 2, 1, true>

Definition at line 446 of file multi_channel_2d_comparison_feature_handler.h.

ScaledRGBD2DComparisonFeatureHandler

using pcl::ScaledRGBD2DComparisonFeatureHandler = typedef ScaledMultiChannel2DComparisonFeatureHandler<float, 4, 3, true>

Definition at line 448 of file multi_channel_2d_comparison_feature_handler.h.

TextureMeshConstPtr

using pcl::TextureMeshConstPtr = typedef TextureMesh::ConstPtr

Definition at line 112 of file TextureMesh.h.

TextureMeshPtr

using pcl::TextureMeshPtr = typedef TextureMesh::Ptr

Definition at line 111 of file TextureMesh.h.

uindex_t

using pcl::uindex_t = typedef detail::int_type_t<detail::index_type_size, false>

Type used for an unsigned index in PCL.

Unsigned index that mirrors the type of the index_t

Definition at line 120 of file types.h.

Vector2fMap

using pcl::Vector2fMap = typedef Eigen::Map<Eigen::Vector2f>

Definition at line 193 of file point_types.hpp.

Vector2fMapConst

using pcl::Vector2fMapConst = typedef const Eigen::Map<const Eigen::Vector2f>

Definition at line 194 of file point_types.hpp.

Vector3c

using pcl::Vector3c = typedef Eigen::Matrix<std::uint8_t, 3, 1>

Definition at line 204 of file point_types.hpp.

Vector3cMap

using pcl::Vector3cMap = typedef Eigen::Map<Vector3c>

Definition at line 205 of file point_types.hpp.

Vector3cMapConst

using pcl::Vector3cMapConst = typedef const Eigen::Map<const Vector3c>

Definition at line 206 of file point_types.hpp.

Vector3fMap

using pcl::Vector3fMap = typedef Eigen::Map<Eigen::Vector3f>

Definition at line 199 of file point_types.hpp.

Vector3fMapConst

using pcl::Vector3fMapConst = typedef const Eigen::Map<const Eigen::Vector3f>

Definition at line 200 of file point_types.hpp.

Vector4c

using pcl::Vector4c = typedef Eigen::Matrix<std::uint8_t, 4, 1>

Definition at line 207 of file point_types.hpp.

Vector4cMap

using pcl::Vector4cMap = typedef Eigen::Map<Vector4c, Eigen::Aligned>

Definition at line 208 of file point_types.hpp.

Vector4cMapConst

using pcl::Vector4cMapConst = typedef const Eigen::Map<const Vector4c, Eigen::Aligned>

Definition at line 209 of file point_types.hpp.

Vector4fMap

using pcl::Vector4fMap = typedef Eigen::Map<Eigen::Vector4f, Eigen::Aligned>

Definition at line 201 of file point_types.hpp.

Vector4fMapConst

using pcl::Vector4fMapConst = typedef const Eigen::Map<const Eigen::Vector4f, Eigen::Aligned>

Definition at line 202 of file point_types.hpp.

VectorAverage2f

using pcl::VectorAverage2f = typedef VectorAverage<float, 2>

Definition at line 116 of file vector_average.h.

VectorAverage3f

using pcl::VectorAverage3f = typedef VectorAverage<float, 3>

Definition at line 117 of file vector_average.h.

VectorAverage4f

using pcl::VectorAverage4f = typedef VectorAverage<float, 4>

Definition at line 118 of file vector_average.h.

VerticesConstPtr

using pcl::VerticesConstPtr = typedef Vertices::ConstPtr

Definition at line 27 of file Vertices.h.

VerticesPtr

using pcl::VerticesPtr = typedef Vertices::Ptr

Definition at line 26 of file Vertices.h.

ViridisLUT

using pcl::ViridisLUT = typedef ColorLUT<pcl::LUT_VIRIDIS>

Definition at line 87 of file colors.h.

void_t

template<typename ... >

using pcl::void_t = typedef void

Definition at line 255 of file type_traits.h.

Enumeration Type Documentation

ColorLUTName

enum pcl::ColorLUTName

Enumerator
LUT_GLASBEY	Color lookup table consisting of 256 colors structured in a maximally discontinuous manner. Generated using the method of Glasbey et al. (see https://github.com/taketwo/glasbey)
LUT_VIRIDIS	A perceptually uniform colormap created by Stéfan van der Walt and Nathaniel Smith for the Python matplotlib library. (see https://youtu.be/xAoljeRJ3lU for background and overview)

Definition at line 52 of file colors.h.

HistogramInterpolationMethod

enum pcl::HistogramInterpolationMethod

Different histogram interpolation methods.

Enumerator
INTERP_NONE	no interpolation
INTERP_TRILINEAR	trilinear interpolation
INTERP_QUADRILINEAR	quadrilinear interpolation

Definition at line 46 of file gasd.h.

InterpolationType

enum pcl::InterpolationType

Enumerator
BORDER_CONSTANT
BORDER_REPLICATE
BORDER_REFLECT
BORDER_WRAP
BORDER_REFLECT_101
BORDER_TRANSPARENT
BORDER_DEFAULT

Definition at line 254 of file io.h.

MorphologicalOperators

enum pcl::MorphologicalOperators

Enumerator
MORPH_OPEN
MORPH_CLOSE
MORPH_DILATE
MORPH_ERODE

Definition at line 49 of file morphological_filter.h.

SacModel

enum pcl::SacModel

Enumerator
SACMODEL_PLANE
SACMODEL_LINE
SACMODEL_CIRCLE2D
SACMODEL_CIRCLE3D
SACMODEL_SPHERE
SACMODEL_CYLINDER
SACMODEL_CONE
SACMODEL_TORUS
SACMODEL_PARALLEL_LINE
SACMODEL_PERPENDICULAR_PLANE
SACMODEL_PARALLEL_LINES
SACMODEL_NORMAL_PLANE
SACMODEL_NORMAL_SPHERE
SACMODEL_REGISTRATION
SACMODEL_REGISTRATION_2D
SACMODEL_PARALLEL_PLANE
SACMODEL_NORMAL_PARALLEL_PLANE
SACMODEL_STICK
SACMODEL_ELLIPSE3D

Definition at line 45 of file model_types.h.

Function Documentation

aligned_free()

void pcl::aligned_free ( void *  ptr )

inline

Definition at line 408 of file pcl_macros.h.

Referenced by pcl::EnergyMaps::releaseAll(), and pcl::LinearizedMaps::releaseAll().

aligned_malloc()

void* pcl::aligned_malloc ( std::size_t  size )

inline

Definition at line 386 of file pcl_macros.h.

Referenced by pcl::EnergyMaps::initialize(), and pcl::LinearizedMaps::initialize().

approximatePolygon()

template<typename PointT >

void pcl::approximatePolygon	(	const PlanarPolygon< PointT > &	polygon,
		PlanarPolygon< PointT > &	approx_polygon,
		float	threshold,
		bool	refine = false,
		bool	closed = true
	)

see approximatePolygon2D

Author

Suat Gedikli gedik.nosp@m.li@w.nosp@m.illow.nosp@m.gara.nosp@m.ge.co.nosp@m.m

Definition at line 44 of file polygon_operations.hpp.

References pcl::PlanarPolygon< PointT >::getCoefficients(), pcl::PlanarPolygon< PointT >::getContour(), pcl::PointCloud< PointT >::resize(), and pcl::PointCloud< PointT >::size().

approximatePolygon2D()

template<typename PointT >

void pcl::approximatePolygon2D	(	const typename PointCloud< PointT >::VectorType &	polygon,
		typename PointCloud< PointT >::VectorType &	approx_polygon,
		float	threshold,
		bool	refine = false,
		bool	closed = true
	)

returns an approximate polygon to given 2D contour.

Uses just X and Y values.

Note

if refinement is not turned on, the resulting polygon will contain points from the original contour with their original z values (if any)

if refinement is turned on, the z values of the refined polygon are not valid and should be set to 0 if point contains z attribute.

Parameters

[in]	polygon	input polygon
[out]	approx_polygon	approximate polygon
[in]	threshold	maximum allowed distance of an input vertex to an output edge
	refine
[in]	closed	whether it is a closed polygon or a polyline

Author

Suat Gedikli gedik.nosp@m.li@w.nosp@m.illow.nosp@m.gara.nosp@m.ge.co.nosp@m.m

Definition at line 80 of file polygon_operations.hpp.

References pcl::PointCloud< PointT >::clear(), pcl::geometry::distance(), eigen22(), M_SQRT1_2, pcl::PointCloud< PointT >::push_back(), pcl::PointCloud< PointT >::reserve(), and pcl::PointCloud< PointT >::size().

checkCoordinateSystem() [1/2]

template<typename Scalar >

bool pcl::checkCoordinateSystem ( const Eigen::Matrix< Scalar, 3, 1 > &  origin, const Eigen::Matrix< Scalar, 3, 1 > &  x_direction, const Eigen::Matrix< Scalar, 3, 1 > &  y_direction, const Scalar  norm_limit = 1e-3, const Scalar  dot_limit = 1e-3  )

inline

Check coordinate system integrity.

Parameters

[in]	origin	the origin of the coordinate system
[in]	x_direction	the first axis
[in]	y_direction	the second axis
[in]	norm_limit	the limit to ignore norm rounding errors
[in]	dot_limit	the limit to ignore dot product rounding errors

Returns

True if the coordinate system is consistent, false otherwise.

Read the other variant for more information

Definition at line 498 of file eigen.h.

checkCoordinateSystem() [2/2]

template<typename Scalar >

bool pcl::checkCoordinateSystem	(	const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &	line_x,
		const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &	line_y,
		const Scalar	norm_limit = 1e-3,
		const Scalar	dot_limit = 1e-3
	)

Check coordinate system integrity.

Parameters

[in]	line_x	the first axis
[in]	line_y	the second axis
[in]	norm_limit	the limit to ignore norm rounding errors
[in]	dot_limit	the limit to ignore dot product rounding errors

Returns

True if the coordinate system is consistent, false otherwise.

Lines must be filled in this form:
line[0-2] = Origin coordinates of the vector
line[3-5] = Direction vector

Can be used like this :
line_x = X axis and line_y = Y axis
line_x = Z axis and line_y = X axis
line_x = Y axis and line_y = Z axis
Because X^Y = Z, Z^X = Y and Y^Z = X. Do NOT invert line order !

Determine whether a coordinate system is consistent or not by checking :
Line origins: They must be the same for the 2 lines
Norm: The 2 lines must be normalized
Dot products: Must be 0 or perpendicular vectors

Definition at line 798 of file eigen.hpp.

Referenced by transformBetween2CoordinateSystems().

comparePair()

bool pcl::comparePair ( std::pair< float, int >  i, std::pair< float, int >  j  )

inline

This function is used as a comparator for sorting.

Definition at line 340 of file region_growing.h.

Referenced by pcl::RegionGrowingRGB< PointT, NormalT >::applyRegionMergingAlgorithm(), pcl::RegionGrowing< PointT, NormalT >::applySmoothRegionGrowingAlgorithm(), and pcl::RegionGrowingRGB< PointT, NormalT >::findRegionNeighbours().

compute3DCentroid() [1/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Vector4d &  centroid  )

inline

Definition at line 133 of file centroid.h.

compute3DCentroid() [2/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Vector4f &  centroid  )

inline

Definition at line 125 of file centroid.h.

compute3DCentroid() [3/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Vector4d &  centroid  )

inline

Definition at line 164 of file centroid.h.

compute3DCentroid() [4/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Vector4f &  centroid  )

inline

Definition at line 156 of file centroid.h.

compute3DCentroid() [5/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, Eigen::Vector4d &  centroid  )

inline

Definition at line 103 of file centroid.h.

compute3DCentroid() [6/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud, Eigen::Vector4f &  centroid  )

inline

Definition at line 96 of file centroid.h.

compute3DCentroid() [7/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( ConstCloudIterator< PointT > &  cloud_iterator, Eigen::Vector4d &  centroid  )

inline

Definition at line 77 of file centroid.h.

compute3DCentroid() [8/8]

template<typename PointT >

unsigned int pcl::compute3DCentroid ( ConstCloudIterator< PointT > &  cloud_iterator, Eigen::Vector4f &  centroid  )

inline

Definition at line 70 of file centroid.h.

computeCovarianceMatrix() [1/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 198 of file centroid.h.

computeCovarianceMatrix() [2/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 190 of file centroid.h.

computeCovarianceMatrix() [3/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 268 of file centroid.h.

computeCovarianceMatrix() [4/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 259 of file centroid.h.

computeCovarianceMatrix() [5/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 552 of file centroid.h.

computeCovarianceMatrix() [6/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 544 of file centroid.h.

computeCovarianceMatrix() [7/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 305 of file centroid.h.

computeCovarianceMatrix() [8/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 296 of file centroid.h.

computeCovarianceMatrix() [9/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 585 of file centroid.h.

computeCovarianceMatrix() [10/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 577 of file centroid.h.

computeCovarianceMatrix() [11/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 520 of file centroid.h.

computeCovarianceMatrix() [12/12]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 513 of file centroid.h.

computeCovarianceMatrixNormalized() [1/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 232 of file centroid.h.

computeCovarianceMatrixNormalized() [2/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 224 of file centroid.h.

computeCovarianceMatrixNormalized() [3/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 344 of file centroid.h.

computeCovarianceMatrixNormalized() [4/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 335 of file centroid.h.

computeCovarianceMatrixNormalized() [5/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, const Eigen::Vector4d &  centroid, Eigen::Matrix3d &  covariance_matrix  )

inline

Definition at line 382 of file centroid.h.

computeCovarianceMatrixNormalized() [6/6]

template<typename PointT >

unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, const Eigen::Vector4f &  centroid, Eigen::Matrix3f &  covariance_matrix  )

inline

Definition at line 373 of file centroid.h.

computeCPPFPairFeature()

PCL_EXPORTS bool pcl::computeCPPFPairFeature	(	const Eigen::Vector4f &	p1,
		const Eigen::Vector4f &	n1,
		const Eigen::Vector4i &	c1,
		const Eigen::Vector4f &	p2,
		const Eigen::Vector4f &	n2,
		const Eigen::Vector4i &	c2,
		float &	f1,
		float &	f2,
		float &	f3,
		float &	f4,
		float &	f5,
		float &	f6,
		float &	f7,
		float &	f8,
		float &	f9,
		float &	f10
	)

Parameters

[in]	p1
[in]	n1
[in]	p2
[in]	n2
[in]	c1
[in]	c2
[out]	f1
[out]	f2
[out]	f3
[out]	f4
[out]	f5
[out]	f6
[out]	f7
[out]	f8
[out]	f9
[out]	f10

computeMeanAndCovarianceMatrix() [1/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Matrix3d &  covariance_matrix, Eigen::Vector4d &  centroid  )

inline

Definition at line 452 of file centroid.h.

computeMeanAndCovarianceMatrix() [2/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::Matrix3f &  covariance_matrix, Eigen::Vector4f &  centroid  )

inline

Definition at line 443 of file centroid.h.

computeMeanAndCovarianceMatrix() [3/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Matrix3d &  covariance_matrix, Eigen::Vector4d &  centroid  )

inline

Definition at line 489 of file centroid.h.

computeMeanAndCovarianceMatrix() [4/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::Matrix3f &  covariance_matrix, Eigen::Vector4f &  centroid  )

inline

Definition at line 480 of file centroid.h.

computeMeanAndCovarianceMatrix() [5/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, Eigen::Matrix3d &  covariance_matrix, Eigen::Vector4d &  centroid  )

inline

Definition at line 416 of file centroid.h.

computeMeanAndCovarianceMatrix() [6/6]

template<typename PointT >

unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud, Eigen::Matrix3f &  covariance_matrix, Eigen::Vector4f &  centroid  )

inline

Definition at line 408 of file centroid.h.

computeMedian()

template<typename IteratorT >

auto pcl::computeMedian ( IteratorT  begin, IteratorT  end  ) -> typename std::iterator_traits<IteratorT>::value_type

inlinenoexcept

Compute the median of a list of values (fast).

See the other overloaded function for more information.

Definition at line 309 of file common.h.

References computeMedian().

computeNDCentroid() [1/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::VectorXd &  centroid  )

inline

Definition at line 972 of file centroid.h.

computeNDCentroid() [2/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, const Indices &  indices, Eigen::VectorXf &  centroid  )

inline

Definition at line 964 of file centroid.h.

computeNDCentroid() [3/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::VectorXd &  centroid  )

inline

Definition at line 1000 of file centroid.h.

computeNDCentroid() [4/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, const pcl::PointIndices &  indices, Eigen::VectorXf &  centroid  )

inline

Definition at line 992 of file centroid.h.

computeNDCentroid() [5/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, Eigen::VectorXd &  centroid  )

inline

Definition at line 945 of file centroid.h.

computeNDCentroid() [6/6]

template<typename PointT >

void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud, Eigen::VectorXf &  centroid  )

inline

Definition at line 938 of file centroid.h.

computePPFPairFeature()

PCL_EXPORTS bool pcl::computePPFPairFeature	(	const Eigen::Vector4f &	p1,
		const Eigen::Vector4f &	n1,
		const Eigen::Vector4f &	p2,
		const Eigen::Vector4f &	n2,
		float &	f1,
		float &	f2,
		float &	f3,
		float &	f4
	)

Parameters

[in]	p1
[in]	n1
[in]	p2
[in]	n2
[out]	f1
[out]	f2
[out]	f3
[out]	f4

computeRGBPairFeatures()

PCL_EXPORTS bool pcl::computeRGBPairFeatures	(	const Eigen::Vector4f &	p1,
		const Eigen::Vector4f &	n1,
		const Eigen::Vector4i &	colors1,
		const Eigen::Vector4f &	p2,
		const Eigen::Vector4f &	n2,
		const Eigen::Vector4i &	colors2,
		float &	f1,
		float &	f2,
		float &	f3,
		float &	f4,
		float &	f5,
		float &	f6,
		float &	f7
	)

Referenced by pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computePointPFHRGBSignature(), and pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computeRGBPairFeatures().

computeRoots()

template<typename Matrix , typename Roots >

void pcl::computeRoots ( const Matrix &  m, Roots &  roots  )

inline

computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues

Parameters

[in]	m	input matrix
[out]	roots	roots of the characteristic polynomial of the input matrix m, which are the eigenvalues

Definition at line 68 of file eigen.hpp.

References computeRoots2().

Referenced by pcl::VectorAverage< real, dimension >::doPCA(), and eigen33().

computeRoots2()

template<typename Scalar , typename Roots >

void pcl::computeRoots2 ( const Scalar &  b, const Scalar &  c, Roots &  roots  )

inline

Compute the roots of a quadratic polynom x^2 + b*x + c = 0.

Parameters

[in]	b	linear parameter
[in]	c	constant parameter
[out]	roots	solutions of x^2 + b*x + c = 0

Definition at line 53 of file eigen.hpp.

Referenced by computeRoots().

copyStringValue() [1/2]

template<typename Type >

void pcl::copyStringValue ( const std::string &  st, pcl::PCLPointCloud2 &  cloud, pcl::index_t  point_index, unsigned int  field_idx, unsigned int  fields_count  )

inline

Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string.

Uses istringstream to do the conversion in classic locale Checks if the st is "nan" and converts it accordingly.

Parameters

[in]	st	the string containing the value to convert and copy
[out]	cloud	the cloud to copy it to
[in]	point_index	the index of the point
[in]	field_idx	the index of the dimension/field
[in]	fields_count	the current fields count

Definition at line 420 of file file_io.h.

copyStringValue() [2/2]

template<typename Type >

void pcl::copyStringValue ( const std::string &  st, pcl::PCLPointCloud2 &  cloud, pcl::index_t  point_index, unsigned int  field_idx, unsigned int  fields_count, std::istringstream &  is  )

inline

Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string.

Uses the provided istringstream to do the conversion, respecting its locale settings Checks if the st is "nan" and converts it accordingly.

Parameters

[in]	st	the string containing the value to convert and copy
[out]	cloud	the cloud to copy it to
[in]	point_index	the index of the point
[in]	field_idx	the index of the dimension/field
[in]	fields_count	the current fields count
[in,out]	is	input string stream for helping to convert st into cloud

Definition at line 440 of file file_io.h.

copyValueString() [1/2]

template<typename Type >

std::enable_if_t<std::is_floating_point<Type>::value> pcl::copyValueString ( const pcl::PCLPointCloud2 &  cloud, const pcl::index_t  point_index, const int  point_size, const unsigned int  field_idx, const unsigned int  fields_count, std::ostream &  stream  )

inline

inserts a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream.

If the value is NaN, it inserts "nan".

Parameters

[in]	cloud	the cloud to copy from
[in]	point_index	the index of the point
[in]	point_size	the size of the point in the cloud
[in]	field_idx	the index of the dimension/field
[in]	fields_count	the current fields count
[out]	stream	the ostringstream to copy into

Definition at line 237 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

copyValueString() [2/2]

template<typename Type >

std::enable_if_t<std::is_integral<Type>::value> pcl::copyValueString ( const pcl::PCLPointCloud2 &  cloud, const pcl::index_t  point_index, const int  point_size, const unsigned int  field_idx, const unsigned int  fields_count, std::ostream &  stream  )

inline

Definition at line 254 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

copyValueString< std::int8_t >()

template<>

void pcl::copyValueString< std::int8_t > ( const pcl::PCLPointCloud2 &  cloud, const pcl::index_t  point_index, const int  point_size, const unsigned int  field_idx, const unsigned int  fields_count, std::ostream &  stream  )

inline

Definition at line 266 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

copyValueString< std::uint8_t >()

template<>

void pcl::copyValueString< std::uint8_t > ( const pcl::PCLPointCloud2 &  cloud, const pcl::index_t  point_index, const int  point_size, const unsigned int  field_idx, const unsigned int  fields_count, std::ostream &  stream  )

inline

Definition at line 280 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

createMapping()

template<typename PointT >

void pcl::createMapping	(	const std::vector< pcl::PCLPointField > &	msg_fields,
		MsgFieldMap &	field_map
	)

Todo:

One could construct a pathological case where the struct has a field where the serialized data has padding

Definition at line 189 of file conversions.h.

References pcl::detail::fieldOrdering().

demeanPointCloud() [1/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Eigen::Vector4d &	centroid,
		Eigen::MatrixXd &	cloud_out
	)

Definition at line 822 of file centroid.h.

demeanPointCloud() [2/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Eigen::Vector4f &	centroid,
		Eigen::MatrixXf &	cloud_out
	)

Definition at line 814 of file centroid.h.

demeanPointCloud() [3/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		const Eigen::Vector4d &	centroid,
		Eigen::MatrixXd &	cloud_out
	)

Definition at line 854 of file centroid.h.

demeanPointCloud() [4/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		const Eigen::Vector4d &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 728 of file centroid.h.

demeanPointCloud() [5/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		const Eigen::Vector4f &	centroid,
		Eigen::MatrixXf &	cloud_out
	)

Definition at line 845 of file centroid.h.

demeanPointCloud() [6/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		const Eigen::Vector4f &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 719 of file centroid.h.

demeanPointCloud() [7/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		const Eigen::Vector4d &	centroid,
		Eigen::MatrixXd &	cloud_out
	)

Definition at line 887 of file centroid.h.

demeanPointCloud() [8/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		const Eigen::Vector4d &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 759 of file centroid.h.

demeanPointCloud() [9/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		const Eigen::Vector4f &	centroid,
		Eigen::MatrixXf &	cloud_out
	)

Definition at line 878 of file centroid.h.

demeanPointCloud() [10/16]

template<typename PointT >

void pcl::demeanPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		const Eigen::Vector4f &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 750 of file centroid.h.

demeanPointCloud() [11/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4d &	centroid,
		Eigen::MatrixXd &	cloud_out,
		int	npts = 0
	)

Definition at line 792 of file centroid.h.

demeanPointCloud() [12/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4d &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 698 of file centroid.h.

demeanPointCloud() [13/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4d &	centroid,
		pcl::PointCloud< PointT > &	cloud_out,
		int	npts = 0
	)

Definition at line 670 of file centroid.h.

demeanPointCloud() [14/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4f &	centroid,
		Eigen::MatrixXf &	cloud_out,
		int	npts = 0
	)

Definition at line 783 of file centroid.h.

demeanPointCloud() [15/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4f &	centroid,
		pcl::PointCloud< PointT > &	cloud_out
	)

Definition at line 690 of file centroid.h.

demeanPointCloud() [16/16]

template<typename PointT >

void pcl::demeanPointCloud	(	ConstCloudIterator< PointT > &	cloud_iterator,
		const Eigen::Vector4f &	centroid,
		pcl::PointCloud< PointT > &	cloud_out,
		int	npts = 0
	)

Definition at line 661 of file centroid.h.

doStereoPeakFilter()

template<class T >

short int pcl::doStereoPeakFilter ( const T *const  acc, short int  dbest, int  peak_filter, int  maxdisp  )

inline

Definition at line 68 of file stereo_matching.h.

doStereoRatioFilter()

template<class T >

short int pcl::doStereoRatioFilter	(	const T *const	acc,
		short int	dbest,
		T	sad_min,
		int	ratio_filter,
		int	maxdisp,
		int	precision = 100
	)

Definition at line 48 of file stereo_matching.h.

estimateProjectionMatrix()

template<typename PointT >

double pcl::estimateProjectionMatrix	(	typename pcl::PointCloud< PointT >::ConstPtr	cloud,
		Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &	projection_matrix,
		const Indices &	indices = {}
	)

Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]] R = rotation matrix and t = translation vector

Parameters

[in]	cloud	input cloud. Must be organized and from a projective device. e.g. stereo or kinect, ...
[out]	projection_matrix	output projection matrix
[in]	indices	The indices to be used to determine the projection matrix

Returns

the resudial error. A high residual indicates, that the point cloud was not from a projective device.

Definition at line 83 of file projection_matrix.hpp.

References B, pcl::ConstCloudIterator< PointT >::getCurrentPointIndex(), pcl::PointCloud< PointT >::height, pcl::common::internal::makeSymmetric(), and pcl::PointCloud< PointT >::width.

euclideanDistance()

template<typename PointType1 , typename PointType2 >

float pcl::euclideanDistance ( const PointType1 &  p1, const PointType2 &  p2  )

inline

Calculate the euclidean distance between the two given points.

Parameters

[in]	p1	the first point
[in]	p2	the second point

Definition at line 204 of file distances.h.

References squaredEuclideanDistance().

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::bruteForceCorrespondences(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::checkBaseMatch(), pcl::ESFEstimation< PointInT, PointOutT >::computeESF(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::determineBaseMatches(), pcl::ESFEstimation< PointInT, PointOutT >::scale_points_unit_sphere(), pcl::SampleConsensusInitialAlignment< PointSource, PointTarget, FeatureT >::selectSamples(), and pcl::TextureMapping< PointInT >::showOcclusions().

for_each_type()

template<typename Sequence , typename F >

void pcl::for_each_type ( F  f )

inline

Definition at line 91 of file for_each_type.h.

fromPCLPointCloud2() [1/3]

template<typename PointT >

void pcl::fromPCLPointCloud2	(	const pcl::PCLPointCloud2 &	msg,
		pcl::PointCloud< PointT > &	cloud
	)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.

Parameters

[in]	msg	the PCLPointCloud2 binary blob
[out]	cloud	the resultant pcl::PointCloud<T>

Definition at line 320 of file conversions.h.

References pcl::PCLPointCloud2::fields, and fromPCLPointCloud2().

fromPCLPointCloud2() [2/3]

template<typename PointT >

void pcl::fromPCLPointCloud2	(	const pcl::PCLPointCloud2 &	msg,
		pcl::PointCloud< PointT > &	cloud,
		const MsgFieldMap &	field_map
	)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.

Parameters

[in]	msg	the PCLPointCloud2 binary blob
[out]	cloud	the resultant pcl::PointCloud<T>
[in]	field_map	a MsgFieldMap object

Note

Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) directly or create you own MsgFieldMap using:

MsgFieldMap field_map;
createMapping<PointT> (msg.fields, field_map);

Definition at line 309 of file conversions.h.

References pcl::PCLPointCloud2::data, and fromPCLPointCloud2().

fromPCLPointCloud2() [3/3]

template<typename PointT >

void pcl::fromPCLPointCloud2	(	const pcl::PCLPointCloud2 &	msg,
		pcl::PointCloud< PointT > &	cloud,
		const MsgFieldMap &	field_map,
		const std::uint8_t *	msg_data
	)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.

Parameters

[in]	msg	the PCLPointCloud2 binary blob (note that the binary point data in msg.data will not be used!)
[out]	cloud	the resultant pcl::PointCloud<T>
[in]	field_map	a MsgFieldMap object
[in]	msg_data	pointer to binary blob data, used instead of msg.data

Note

Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) instead, except if you have a binary blob of point data that you do not want to copy into a pcl::PCLPointCloud2 in order to use fromPCLPointCloud2.

Definition at line 229 of file conversions.h.

References pcl::PointCloud< PointT >::data(), pcl::PCLPointCloud2::fields, pcl::PCLPointCloud2::header, pcl::PointCloud< PointT >::header, pcl::PCLPointCloud2::height, pcl::PointCloud< PointT >::height, pcl::PCLPointCloud2::is_dense, pcl::PointCloud< PointT >::is_dense, pcl::PCLPointCloud2::point_step, pcl::PointCloud< PointT >::resize(), pcl::PCLPointCloud2::row_step, pcl::PCLPointCloud2::width, and pcl::PointCloud< PointT >::width.

Referenced by fromPCLPointCloud2(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::getMeshesFromTSDFVector(), pcl::TextureMapping< PointInT >::mapMultipleTexturesToMeshUV(), pcl::ImageGrabber< PointT >::operator[](), pcl::PCDGrabber< PointT >::operator[](), pcl::ImageGrabber< PointT >::publish(), pcl::StereoGrabber< PointT >::publish(), pcl::PCDGrabber< PointT >::publish(), pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::queryBBIncludes(), pcl::IFSReader::read(), pcl::FileReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), pcl::PLYReader::read(), pcl::TextureMapping< PointInT >::removeOccludedPoints(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::runMarchingCubes(), pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals(), pcl::registration::CorrespondenceEstimationNormalShooting< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setSourceNormals(), pcl::registration::CorrespondenceRejectorDistance::setSourcePoints(), pcl::registration::CorrespondenceRejectorMedianDistance::setSourcePoints(), pcl::registration::CorrespondenceRejectionOrganizedBoundary::setSourcePoints(), pcl::registration::CorrespondenceRejectorPoly< SourceT, TargetT >::setSourcePoints(), pcl::registration::CorrespondenceRejectorSampleConsensus< PointT >::setSourcePoints(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setSourcePoints(), pcl::registration::CorrespondenceRejectorVarTrimmed::setSourcePoints(), pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setTargetNormals(), pcl::registration::CorrespondenceRejectorDistance::setTargetPoints(), pcl::registration::CorrespondenceRejectorMedianDistance::setTargetPoints(), pcl::registration::CorrespondenceRejectionOrganizedBoundary::setTargetPoints(), pcl::registration::CorrespondenceRejectorPoly< SourceT, TargetT >::setTargetPoints(), pcl::registration::CorrespondenceRejectorSampleConsensus< PointT >::setTargetPoints(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setTargetPoints(), pcl::registration::CorrespondenceRejectorVarTrimmed::setTargetPoints(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::TextureMapping< PointInT >::sortFacesByCamera(), pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras(), and pcl::geometry::toHalfEdgeMesh().

getAllPcdFilesInDirectory()

void pcl::getAllPcdFilesInDirectory ( const std::string &  directory, std::vector< std::string > &  file_names  )

inline

Find all *.pcd files in the directory and return them sorted.

Parameters

directory	the directory to be searched
file_names	the resulting (sorted) list of .pcd files

Definition at line 55 of file file_io.hpp.

getCameraMatrixFromProjectionMatrix()

PCL_EXPORTS void pcl::getCameraMatrixFromProjectionMatrix	(	const Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &	projection_matrix,
		Eigen::Matrix3f &	camera_matrix
	)

Determines the camera matrix from the given projection matrix.

Note

This method does NOT use a RQ decomposition, but uses the fact that the left 3x3 matrix P' of P squared eliminates the rotational part. P' = K * R -> P' * P'^T = K * R * R^T * K = K * K^T

Parameters

[in]	projection_matrix
[out]	camera_matrix

Referenced by pcl::search::OrganizedNeighbor< PointT >::computeCameraMatrix().

getFieldIndex()

template<typename PointT >

int pcl::getFieldIndex	(	const pcl::PointCloud< PointT > &	,
		const std::string &	field_name,
		std::vector< pcl::PCLPointField > &	fields
	)

Definition at line 52 of file io.hpp.

Referenced by pcl::OrganizedFastMesh< PointInT >::performReconstruction(), and pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::sortOctantIndices().

getFields() [1/2]

template<typename PointT >

void pcl::getFields	(	const pcl::PointCloud< PointT > &	,
		std::vector< pcl::PCLPointField > &	fields
	)

Definition at line 83 of file io.hpp.

getFields() [2/2]

template<typename PointT >

void pcl::getFields

(

std::vector< pcl::PCLPointField > &

fields

)

Definition at line 90 of file io.hpp.

getFieldsSizes()

PCL_EXPORTS void pcl::getFieldsSizes	(	const std::vector< pcl::PCLPointField > &	fields,
		std::vector< int > &	field_sizes
	)

Obtain a vector with the sizes of all valid fields (e.g., not "_")

Parameters

[in]	fields	the input vector containing the fields
[out]	field_sizes	the resultant field sizes in bytes

getFieldValue()

template<typename PointT , typename ValT >

void pcl::getFieldValue ( const PointT &  pt, std::size_t  field_offset, ValT &  value  )

inline

Get the value at a specified field in a point.

Parameters

[in]	pt	the point to get the value from
[in]	field_offset	the offset of the field
[out]	value	the value to retrieve

Definition at line 249 of file type_traits.h.

getFileExtension()

std::string pcl::getFileExtension ( const std::string &  input )

inline

Get the file extension from the given string (the remaining string after the last '.

')

Parameters

input

the input filename

Returns

input 's file extension

Definition at line 89 of file file_io.hpp.

getFilenameWithoutExtension()

std::string pcl::getFilenameWithoutExtension ( const std::string &  input )

inline

Remove the extension from the given string and return only the filename (everything before the last '.

')

Parameters

input

the input filename (with the file extension)

Returns

the resulting filename, stripped of its extension

Definition at line 83 of file file_io.hpp.

getFilenameWithoutPath()

std::string pcl::getFilenameWithoutPath ( const std::string &  input )

inline

Remove the path from the given string and return only the filename (the remaining string after the last '/')

Parameters

input

the input filename (with full path)

Returns

the resulting filename, stripped of the path

Definition at line 77 of file file_io.hpp.

getMeanPointDensity() [1/2]

template<typename PointT >

float pcl::getMeanPointDensity ( const typename pcl::PointCloud< PointT >::ConstPtr &  cloud, const pcl::Indices &  indices, float  max_dist, int  nr_threads = 1  )

inline

Compute the mean point density of a given point cloud.

Parameters

[in]	cloud	pointer to the input point cloud
[in]	indices	the vector of point indices to use from cloud
[in]	max_dist	maximum distance of a point to be considered as a neighbor
[in]	nr_threads	number of threads to use (default = 1, only used if OpenMP flag is set)

Returns

the mean point density of a given point cloud

Definition at line 87 of file ia_fpcs.hpp.

References pcl::utils::ignore(), and pcl::search::KdTree< PointT, Tree >::setInputCloud().

getMeanPointDensity() [2/2]

template<typename PointT >

float pcl::getMeanPointDensity ( const typename pcl::PointCloud< PointT >::ConstPtr &  cloud, float  max_dist, int  nr_threads = 1  )

inline

Compute the mean point density of a given point cloud.

Parameters

[in]	cloud	pointer to the input point cloud
[in]	max_dist	maximum distance of a point to be considered as a neighbor
[in]	nr_threads	number of threads to use (default = 1, only used if OpenMP flag is set)

Returns

the mean point density of a given point cloud

Definition at line 54 of file ia_fpcs.hpp.

References pcl::utils::ignore(), pcl::search::KdTree< PointT, Tree >::nearestKSearch(), pcl::search::KdTree< PointT, Tree >::setInputCloud(), and pcl::PointCloud< PointT >::size().

getMinMax3D() [1/4]

PCL_EXPORTS void pcl::getMinMax3D	(	const pcl::PCLPointCloud2ConstPtr &	cloud,
		const Indices &	indices,
		int	x_idx,
		int	y_idx,
		int	z_idx,
		const std::string &	distance_field_name,
		float	min_distance,
		float	max_distance,
		Eigen::Vector4f &	min_pt,
		Eigen::Vector4f &	max_pt,
		bool	limit_negative = false
	)

Obtain the maximum and minimum points in 3D from a given point cloud.

Note

Performs internal data filtering as well.

Parameters

[in]	cloud	the pointer to a pcl::PCLPointCloud2 dataset
[in]	indices	the point cloud indices that need to be considered
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[in]	distance_field_name	the name of the dimension to filter data along to
[in]	min_distance	the minimum acceptable value in distance_field_name data
[in]	max_distance	the maximum acceptable value in distance_field_name data
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point
[in]	limit_negative	false if data inside of the [min_distance; max_distance] interval should be considered, true otherwise.

getMinMax3D() [2/4]

PCL_EXPORTS void pcl::getMinMax3D	(	const pcl::PCLPointCloud2ConstPtr &	cloud,
		const Indices &	indices,
		int	x_idx,
		int	y_idx,
		int	z_idx,
		Eigen::Vector4f &	min_pt,
		Eigen::Vector4f &	max_pt
	)

Obtain the maximum and minimum points in 3D from a given point cloud.

Parameters

[in]	cloud	the pointer to a pcl::PCLPointCloud2 dataset
[in]	indices	the point cloud indices that need to be considered
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point

getMinMax3D() [3/4]

PCL_EXPORTS void pcl::getMinMax3D	(	const pcl::PCLPointCloud2ConstPtr &	cloud,
		int	x_idx,
		int	y_idx,
		int	z_idx,
		const std::string &	distance_field_name,
		float	min_distance,
		float	max_distance,
		Eigen::Vector4f &	min_pt,
		Eigen::Vector4f &	max_pt,
		bool	limit_negative = false
	)

Obtain the maximum and minimum points in 3D from a given point cloud.

Note

Performs internal data filtering as well.

Parameters

[in]	cloud	the pointer to a pcl::PCLPointCloud2 dataset
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[in]	distance_field_name	the name of the dimension to filter data along to
[in]	min_distance	the minimum acceptable value in distance_field_name data
[in]	max_distance	the maximum acceptable value in distance_field_name data
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point
[in]	limit_negative	false if data inside of the [min_distance; max_distance] interval should be considered, true otherwise.

getMinMax3D() [4/4]

PCL_EXPORTS void pcl::getMinMax3D	(	const pcl::PCLPointCloud2ConstPtr &	cloud,
		int	x_idx,
		int	y_idx,
		int	z_idx,
		Eigen::Vector4f &	min_pt,
		Eigen::Vector4f &	max_pt
	)

Obtain the maximum and minimum points in 3D from a given point cloud.

Parameters

[in]	cloud	the pointer to a pcl::PCLPointCloud2 dataset
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point

getPrincipalTransformation() [1/2]

template<typename PointT >

double pcl::getPrincipalTransformation ( const pcl::PointCloud< PointT > &  cloud, Eigen::Affine3f &  transform  )

inline

Definition at line 499 of file transforms.h.

getPrincipalTransformation() [2/2]

template<typename PointT , typename Scalar >

double pcl::getPrincipalTransformation ( const pcl::PointCloud< PointT > &  cloud, Eigen::Transform< Scalar, 3, Eigen::Affine > &  transform  )

inline

Calculates the principal (PCA-based) alignment of the point cloud.

Parameters

[in]	cloud	the input point cloud
[out]	transform	the resultant transform

Returns

the ratio lambda1/lambda2 or lambda2/lambda3, whatever is closer to 1.

Note

If the return value is close to one then the transformation might be not unique -> two principal directions have almost same variance (extend)

Definition at line 495 of file transforms.hpp.

References computeMeanAndCovarianceMatrix(), and eigen33().

getRandomColor()

PCL_EXPORTS RGB pcl::getRandomColor	(	double	min = 0.2,
		double	max = 2.8
	)

getRejectedQueryIndices()

void pcl::getRejectedQueryIndices	(	const pcl::Correspondences &	correspondences_before,
		const pcl::Correspondences &	correspondences_after,
		Indices &	indices,
		bool	presorting_required = true
	)

Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection.

Parameters

[in]	correspondences_before	Vector of correspondences before rejection
[in]	correspondences_after	Vector of correspondences after rejection
[out]	indices	Query point indices of correspondences that have been rejected
[in]	presorting_required	Enable/disable internal sorting of vectors. By default (true), vectors are internally sorted before determining their difference. If the order of correspondences in correspondences_after is not different (has not been changed) from the order in correspondences_before this pre-processing step can be disabled in order to gain efficiency. In order to disable pre-sorting set presorting_required to false.

Referenced by pcl::registration::CorrespondenceRejector::getRejectedQueryIndices().

getTime()

double pcl::getTime ( )

inline

Definition at line 186 of file time.h.

getTimestamp()

PCL_EXPORTS std::string pcl::getTimestamp ( const std::chrono::time_point< std::chrono::system_clock > &  time = std::chrono::system_clock::now() )

inline

Returns a timestamp in local time as string formatted like boosts to_iso_string see https://www.boost.org/doc/libs/1_81_0/doc/html/date_time/posix_time.html#ptime_to_string Example: 19750101T235959.123456.

Parameters

time	std::chrono::timepoint to convert, defaults to now

Returns

std::string containing the timestamp

Definition at line 25 of file timestamp.h.

getTransformation() [1/2]

void pcl::getTransformation ( double  x, double  y, double  z, double  roll, double  pitch, double  yaw, Eigen::Affine3d &  t  )

inline

Definition at line 299 of file eigen.h.

getTransformation() [2/2]

void pcl::getTransformation ( float  x, float  y, float  z, float  roll, float  pitch, float  yaw, Eigen::Affine3f &  t  )

inline

Definition at line 292 of file eigen.h.

interpolatePointIndex()

PCL_EXPORTS int pcl::interpolatePointIndex	(	int	p,
		int	length,
		InterpolationType	type
	)

Returns

the right index according to the interpolation type.

Note

this is adapted from OpenCV

Parameters

p	the index of point to interpolate
length	the top/bottom row or left/right column index
type	the requested interpolation

Exceptions

pcl::BadArgumentException

if type is unknown

Referenced by copyPointCloud().

isFinite()

template<typename PointT >

bool pcl::isFinite ( const PointT &  pt )

inline

Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if finite, false otherwise.

Definition at line 55 of file point_tests.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::addPointIdx(), pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::addPointsFromInputCloud(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::io::OrganizedPointCloudCompression< PointT >::analyzeOrganizedCloud(), pcl::CropBox< PointT >::applyFilter(), pcl::MedianFilter< PointT >::applyFilter(), pcl::LocalMaximum< PointT >::applyFilterIndices(), pcl::ModelOutlierRemoval< PointT >::applyFilterIndices(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::approxNearestSearch(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::bilinearInterpolation(), pcl::PyramidFeatureHistogram< PointFeature >::compute(), pcl::filters::Pyramid< PointT >::compute(), compute3DCentroid(), pcl::GrabCut< PointT >::computeBetaNonOrganized(), computeCentroid(), computeCentroidAndOBB(), computeCovarianceMatrix(), pcl::SHOTEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::IntensityGradientEstimation< PointInT, PointNT, PointOutT, IntensitySelectorT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computeFeature(), pcl::NormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::SHOTColorEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::UniqueShapeContext< PointInT, PointOutT, PointRFT >::computeFeature(), computeMeanAndCovarianceMatrix(), pcl::FLARELocalReferenceFrameEstimation< PointInT, PointNT, PointOutT, SignedDistanceT >::computePointLRF(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::registration::CorrespondenceEstimationOrganizedProjection< PointSource, PointTarget, Scalar >::determineCorrespondences(), pcl::RangeImage::doZBuffer(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::ApproximateProgressiveMorphologicalFilter< PointT >::extract(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::RegionGrowing< PointT, NormalT >::findPointNeighbours(), flipNormalTowardsNormalsMean(), pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::genOctreeKeyforPoint(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::visualization::PointCloudColorHandlerLabelField< PointT >::getColor(), getPointCloudDifference(), pcl::OrganizedFastMesh< PointInT >::isValidQuad(), pcl::OrganizedFastMesh< PointInT >::isValidTriangle(), pcl::search::OrganizedNeighbor< PointT >::nearestKSearch(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::nearestKSearch(), pcl::search::BruteForce< PointT >::nearestKSearch(), pcl::filters::GaussianKernel< PointInT, PointOutT >::operator()(), pcl::filters::GaussianKernelRGB< PointInT, PointOutT >::operator()(), pcl::OrganizedFastMesh< PointInT >::performReconstruction(), pcl::io::pointCloudTovtkStructuredGrid(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::radiusSearch(), pcl::search::OrganizedNeighbor< PointT >::radiusSearch(), pcl::search::BruteForce< PointT >::radiusSearch(), removeNaNNormalsFromPointCloud(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseHarris(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseLowe(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseNoble(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::search::OrganizedNeighbor< PointT >::setInputCloud(), pcl::octree::OctreePointCloudOccupancy< PointT, LeafContainerT, BranchContainerT >::setOccupiedVoxelsAtPointsFromCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), and pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::voxelSearch().

isFinite< pcl::Axis >()

template<>

bool pcl::isFinite< pcl::Axis > ( const pcl::Axis &  )

inline

Definition at line 68 of file point_tests.h.

isFinite< pcl::BorderDescription >()

template<>

bool pcl::isFinite< pcl::BorderDescription > ( const pcl::BorderDescription &  )

inline

Definition at line 70 of file point_tests.h.

isFinite< pcl::Boundary >()

template<>

bool pcl::isFinite< pcl::Boundary > ( const pcl::Boundary &  )

inline

Definition at line 71 of file point_tests.h.

isFinite< pcl::BRISKSignature512 >()

template<>

bool pcl::isFinite< pcl::BRISKSignature512 > ( const pcl::BRISKSignature512 &  )

inline

Definition at line 69 of file point_tests.h.

isFinite< pcl::CPPFSignature >()

template<>

bool pcl::isFinite< pcl::CPPFSignature > ( const pcl::CPPFSignature &  )

inline

Definition at line 72 of file point_tests.h.

isFinite< pcl::ESFSignature640 >()

template<>

bool pcl::isFinite< pcl::ESFSignature640 > ( const pcl::ESFSignature640 &  )

inline

Definition at line 73 of file point_tests.h.

isFinite< pcl::FPFHSignature33 >()

template<>

bool pcl::isFinite< pcl::FPFHSignature33 > ( const pcl::FPFHSignature33 &  )

inline

Definition at line 74 of file point_tests.h.

isFinite< pcl::GASDSignature512 >()

template<>

bool pcl::isFinite< pcl::GASDSignature512 > ( const pcl::GASDSignature512 &  )

inline

Definition at line 75 of file point_tests.h.

isFinite< pcl::GASDSignature7992 >()

template<>

bool pcl::isFinite< pcl::GASDSignature7992 > ( const pcl::GASDSignature7992 &  )

inline

Definition at line 77 of file point_tests.h.

isFinite< pcl::GASDSignature984 >()

template<>

bool pcl::isFinite< pcl::GASDSignature984 > ( const pcl::GASDSignature984 &  )

inline

Definition at line 76 of file point_tests.h.

isFinite< pcl::GRSDSignature21 >()

template<>

bool pcl::isFinite< pcl::GRSDSignature21 > ( const pcl::GRSDSignature21 &  )

inline

Definition at line 78 of file point_tests.h.

isFinite< pcl::Intensity >()

template<>

bool pcl::isFinite< pcl::Intensity > ( const pcl::Intensity &  )

inline

Definition at line 79 of file point_tests.h.

isFinite< pcl::IntensityGradient >()

template<>

bool pcl::isFinite< pcl::IntensityGradient > ( const pcl::IntensityGradient &  )

inline

Definition at line 80 of file point_tests.h.

isFinite< pcl::Label >()

template<>

bool pcl::isFinite< pcl::Label > ( const pcl::Label &  )

inline

Definition at line 81 of file point_tests.h.

isFinite< pcl::MomentInvariants >()

template<>

bool pcl::isFinite< pcl::MomentInvariants > ( const pcl::MomentInvariants &  )

inline

Definition at line 82 of file point_tests.h.

isFinite< pcl::Normal >()

template<>

bool pcl::isFinite< pcl::Normal > ( const pcl::Normal &  n )

inline

Definition at line 111 of file point_tests.h.

isFinite< pcl::NormalBasedSignature12 >()

template<>

bool pcl::isFinite< pcl::NormalBasedSignature12 > ( const pcl::NormalBasedSignature12 &  )

inline

Definition at line 83 of file point_tests.h.

isFinite< pcl::PFHRGBSignature250 >()

template<>

bool pcl::isFinite< pcl::PFHRGBSignature250 > ( const pcl::PFHRGBSignature250 &  )

inline

Definition at line 84 of file point_tests.h.

isFinite< pcl::PFHSignature125 >()

template<>

bool pcl::isFinite< pcl::PFHSignature125 > ( const pcl::PFHSignature125 &  )

inline

Definition at line 85 of file point_tests.h.

isFinite< pcl::PointXY >()

template<>

bool pcl::isFinite< pcl::PointXY > ( const pcl::PointXY &  p )

inline

Definition at line 104 of file point_tests.h.

References pcl::PointXY::x, and pcl::PointXY::y.

isFinite< pcl::PPFRGBSignature >()

template<>

bool pcl::isFinite< pcl::PPFRGBSignature > ( const pcl::PPFRGBSignature &  )

inline

Definition at line 86 of file point_tests.h.

isFinite< pcl::PPFSignature >()

template<>

bool pcl::isFinite< pcl::PPFSignature > ( const pcl::PPFSignature &  pt )

inline

Definition at line 88 of file point_tests.h.

References pcl::PPFSignature::alpha_m, pcl::PPFSignature::f1, pcl::PPFSignature::f2, pcl::PPFSignature::f3, and pcl::PPFSignature::f4.

isFinite< pcl::PrincipalCurvatures >()

template<>

bool pcl::isFinite< pcl::PrincipalCurvatures > ( const pcl::PrincipalCurvatures &  )

inline

Definition at line 93 of file point_tests.h.

isFinite< pcl::PrincipalRadiiRSD >()

template<>

bool pcl::isFinite< pcl::PrincipalRadiiRSD > ( const pcl::PrincipalRadiiRSD &  )

inline

Definition at line 94 of file point_tests.h.

isFinite< pcl::ReferenceFrame >()

template<>

bool pcl::isFinite< pcl::ReferenceFrame > ( const pcl::ReferenceFrame &  )

inline

Definition at line 96 of file point_tests.h.

isFinite< pcl::RGB >()

template<>

bool pcl::isFinite< pcl::RGB > ( const pcl::RGB &  )

inline

Definition at line 95 of file point_tests.h.

isFinite< pcl::ShapeContext1980 >()

template<>

bool pcl::isFinite< pcl::ShapeContext1980 > ( const pcl::ShapeContext1980 &  )

inline

Definition at line 99 of file point_tests.h.

isFinite< pcl::SHOT1344 >()

template<>

bool pcl::isFinite< pcl::SHOT1344 > ( const pcl::SHOT1344 &  )

inline

Definition at line 97 of file point_tests.h.

isFinite< pcl::SHOT352 >()

template<>

bool pcl::isFinite< pcl::SHOT352 > ( const pcl::SHOT352 &  )

inline

Definition at line 98 of file point_tests.h.

isFinite< pcl::UniqueShapeContext1960 >()

template<>

bool pcl::isFinite< pcl::UniqueShapeContext1960 > ( const pcl::UniqueShapeContext1960 &  )

inline

Definition at line 100 of file point_tests.h.

isFinite< pcl::VFHSignature308 >()

template<>

bool pcl::isFinite< pcl::VFHSignature308 > ( const pcl::VFHSignature308 &  )

inline

Definition at line 101 of file point_tests.h.

isNormalFinite() [1/2]

template<typename PointT , traits::HasNoNormal< PointT > = true>

constexpr bool pcl::isNormalFinite ( const PointT &  )

inlineconstexprnoexcept

Definition at line 131 of file point_tests.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), and pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::computePoint().

isNormalFinite() [2/2]

template<typename PointT , traits::HasNormal< PointT > = true>

bool pcl::isNormalFinite ( const PointT &  pt )

inlinenoexcept

Definition at line 150 of file point_tests.h.

isSamePointType()

template<typename Point1T , typename Point2T >

constexpr bool pcl::isSamePointType ( )

constexprnoexcept

Check if two given point types are the same or not.

Definition at line 356 of file io.h.

isValueFinite() [1/2]

template<typename Type >

std::enable_if_t<std::is_integral<Type>::value, bool> pcl::isValueFinite ( const pcl::PCLPointCloud2 &  , const pcl::index_t  , const int  , const unsigned int  , const unsigned int    )

inline

Definition at line 319 of file file_io.h.

isValueFinite() [2/2]

template<typename Type >

std::enable_if_t<std::is_floating_point<Type>::value, bool> pcl::isValueFinite ( const pcl::PCLPointCloud2 &  cloud, const pcl::index_t  point_index, const int  point_size, const unsigned int  field_idx, const unsigned int  fields_count  )

inline

Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not.

Parameters

[in]	cloud	the cloud that contains the data
[in]	point_index	the index of the point
[in]	point_size	the size of the point in the cloud
[in]	field_idx	the index of the dimension/field
[in]	fields_count	the current fields count

Returns

true if the value is finite, false otherwise

Definition at line 306 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

isXYFinite() [1/2]

template<typename PointT , traits::HasNoXY< PointT > = true>

constexpr bool pcl::isXYFinite ( const PointT &  )

inlineconstexprnoexcept

Definition at line 119 of file point_tests.h.

isXYFinite() [2/2]

template<typename PointT , traits::HasXY< PointT > = true>

bool pcl::isXYFinite ( const PointT &  pt )

inlinenoexcept

Definition at line 138 of file point_tests.h.

isXYZFinite() [1/2]

template<typename PointT , traits::HasNoXYZ< PointT > = true>

constexpr bool pcl::isXYZFinite ( const PointT &  )

inlineconstexprnoexcept

Definition at line 125 of file point_tests.h.

Referenced by pcl::UniformSampling< PointT >::applyFilter(), pcl::BilateralFilter< PointT >::applyFilter(), pcl::VoxelGrid< PointT >::applyFilter(), pcl::VoxelGridCovariance< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilterIndices(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::registration::CorrespondenceEstimation< PointSource, PointTarget, Scalar >::determineCorrespondences(), pcl::registration::CorrespondenceEstimation< PointSource, PointTarget, Scalar >::determineReciprocalCorrespondences(), pcl::Registration< PointSource, PointTarget, Scalar >::getFitnessScore(), getMinMax3D(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), and pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi().

isXYZFinite() [2/2]

template<typename PointT , traits::HasXYZ< PointT > = true>

bool pcl::isXYZFinite ( const PointT &  pt )

inlinenoexcept

Definition at line 144 of file point_tests.h.

knn_search()

template<class FlannIndex , class Query , class Indices , class Distances , class SearchParams >

int pcl::knn_search	(	const FlannIndex &	index,
		const Query &	query,
		Indices &	indices,
		Distances &	dists,
		unsigned int	k,
		const SearchParams &	params
	)

Compatibility template function to allow use of various types of indices with FLANN.

Template is used for all params to not constrain any FLANN side capability

Parameters

[in,out]	index	A index searcher, of type ::flann::Index<Dist> or similar, where Dist is a template for computing distance between 2 points
[in]	query	A ::flann::Matrix<float> or compatible matrix representation of the query point
[out]	indices	Neighboring k indices found
[out]	dists	Computed distance matrix
[in]	k	Number of neighbors to search for
[in]	params	Any parameters to pass to the knn_search call

Definition at line 223 of file kdtree_flann.hpp.

Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch().

lzfCompress()

PCL_EXPORTS unsigned int pcl::lzfCompress	(	const void *const	in_data,
		unsigned int	in_len,
		void *	out_data,
		unsigned int	out_len
	)

Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm.

If the output buffer is not large enough or any error occurs return 0, otherwise return the number of bytes used, which might be considerably more than in_len (but less than 104% of the original size), so it makes sense to always use out_len == in_len - 1), to ensure some compression, and store the data uncompressed otherwise (with a flag, of course.

Note

The buffers must not be overlapping.

Parameters

[in]	in_data	the input uncompressed buffer
[in]	in_len	the length of the input buffer
[out]	out_data	the output buffer where the compressed result will be stored
[in]	out_len	the length of the output buffer

Referenced by pcl::PCDWriter::writeBinaryCompressed().

lzfDecompress()

PCL_EXPORTS unsigned int pcl::lzfDecompress	(	const void *const	in_data,
		unsigned int	in_len,
		void *	out_data,
		unsigned int	out_len
	)

Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len.

The result will be stored at out_data up to a maximum of out_len characters.

If the output buffer is not large enough to hold the decompressed data, a 0 is returned and errno is set to E2BIG. Otherwise the number of decompressed bytes (i.e. the original length of the data) is returned.

If an error in the compressed data is detected, a zero is returned and errno is set to EINVAL.

This function is very fast, about as fast as a copying loop.

Parameters

[in]	in_data	the input compressed buffer
[in]	in_len	the length of the input buffer
[out]	out_data	the output buffer (must be resized to out_len)
[in]	out_len	the length of the output buffer

make_shared()

template<typename T , typename ... Args>

shared_ptr<T> pcl::make_shared

(

Args &&...

args

)

Returns a pcl::shared_ptr compliant with type T's allocation policy.

std::allocate_shared or std::make_shared will be invoked in case T has or doesn't have a custom allocator, respectively.

Note

In MSVC < 1915 (before version 15.8) alignment was incorrectly set at most at alignof(max_align_t). This bug was fixed in said version and is acknowledged by defining _ENABLE_EXTENDED_ALIGNED_STORAGE. See #3752.

See also

pcl::has_custom_allocator, PCL_MAKE_ALIGNED_OPERATOR_NEW

Template Parameters

T	Type of the object to create a pcl::shared_ptr of
Args	Types for the arguments to pcl::make_shared

Parameters

args	List of arguments with which an instance of T will be constructed

Returns

pcl::shared_ptr of an instance of type T

Referenced by pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >::setUseSymmetricObjective().

operator<<() [1/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Axis &	p
	)

operator<<() [2/69]

template<typename real >

std::ostream & pcl::operator<<	(	std::ostream &	os,
		const BivariatePolynomialT< real > &	p
	)

Definition at line 237 of file bivariate_polynomial.hpp.

References pcl::BivariatePolynomialT< real >::degree, and pcl::BivariatePolynomialT< real >::parameters.

operator<<() [3/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const BorderDescription &	p
	)

operator<<() [4/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Boundary &	p
	)

operator<<() [5/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const BRISKSignature512 &	p
	)

operator<<() [6/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Correspondence &	c
	)

overloaded << operator

operator<<() [7/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const CPPFSignature &	p
	)

operator<<() [8/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const ESFSignature640 &	p
	)

operator<<() [9/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const FPFHSignature33 &	p
	)

operator<<() [10/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GASDSignature512 &	p
	)

operator<<() [11/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GASDSignature7992 &	p
	)

operator<<() [12/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GASDSignature984 &	p
	)

operator<<() [13/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GFPFHSignature16 &	p
	)

operator<<() [14/69]

std::ostream& pcl::operator<< ( std::ostream &  os, const GradientXY &  p  )

inline

Definition at line 72 of file point_types.h.

References pcl::GradientXY::magnitude, pcl::GradientXY::x, and pcl::GradientXY::y.

operator<<() [15/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GRSDSignature21 &	p
	)

operator<<() [16/69]

template<int N>

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Histogram< N > &	p
	)

Definition at line 1717 of file point_types.hpp.

References pcl::Histogram< N >::histogram, and PCL_IF_CONSTEXPR.

operator<<() [17/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Intensity &	p
	)

operator<<() [18/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Intensity32u &	p
	)

operator<<() [19/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Intensity8u &	p
	)

operator<<() [20/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const IntensityGradient &	p
	)

operator<<() [21/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const InterestPoint &	p
	)

operator<<() [22/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Label &	p
	)

operator<<() [23/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const MomentInvariants &	p
	)

operator<<() [24/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Narf36 &	p
	)

operator<<() [25/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const Normal &	p
	)

operator<<() [26/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const NormalBasedSignature12 &	p
	)

operator<<() [27/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PFHRGBSignature250 &	p
	)

operator<<() [28/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PFHSignature125 &	p
	)

operator<<() [29/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointDEM &	p
	)

operator<<() [30/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointNormal &	p
	)

operator<<() [31/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointSurfel &	p
	)

operator<<() [32/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointUV &	p
	)

operator<<() [33/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointWithRange &	p
	)

operator<<() [34/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointWithScale &	p
	)

operator<<() [35/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointWithViewpoint &	p
	)

operator<<() [36/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXY &	p
	)

operator<<() [37/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZ &	p
	)

operator<<() [38/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZHSV &	p
	)

operator<<() [39/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZI &	p
	)

operator<<() [40/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZINormal &	p
	)

operator<<() [41/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZL &	p
	)

operator<<() [42/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZLAB &	p
	)

operator<<() [43/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZLNormal &	p
	)

operator<<() [44/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZRGB &	p
	)

operator<<() [45/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZRGBA &	p
	)

operator<<() [46/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZRGBL &	p
	)

operator<<() [47/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PointXYZRGBNormal &	p
	)

operator<<() [48/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PPFRGBSignature &	p
	)

operator<<() [49/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PPFSignature &	p
	)

operator<<() [50/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PrincipalCurvatures &	p
	)

operator<<() [51/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PrincipalRadiiRSD &	p
	)

operator<<() [52/69]

std::ostream& pcl::operator<< ( std::ostream &  os, const RangeImage &  r  )

inline

/ingroup range_image

Definition at line 813 of file range_image.h.

References pcl::RangeImage::getAngularResolutionX(), pcl::RangeImage::getAngularResolutionY(), pcl::PointCloud< PointT >::header, pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::is_dense, RAD2DEG, pcl::PointCloud< PointT >::sensor_orientation_, pcl::PointCloud< PointT >::sensor_origin_, pcl::PointCloud< PointT >::size(), and pcl::PointCloud< PointT >::width.

operator<<() [53/69]

std::ostream& pcl::operator<< ( std::ostream &  os, const RangeImageBorderExtractor::Parameters &  p  )

inline

Definition at line 60 of file range_image_border_extractor.hpp.

References pcl::RangeImageBorderExtractor::Parameters::minimum_border_probability, pcl::RangeImageBorderExtractor::Parameters::pixel_radius_border_direction, pcl::RangeImageBorderExtractor::Parameters::pixel_radius_borders, pcl::RangeImageBorderExtractor::Parameters::pixel_radius_plane_extraction, pcl::RangeImageBorderExtractor::Parameters::pixel_radius_principal_curvature, PVARC, and PVARN.

operator<<() [54/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const ReferenceFrame &	p
	)

operator<<() [55/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const RGB &	p
	)

operator<<() [56/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const ShapeContext1980 &	p
	)

operator<<() [57/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const SHOT1344 &	p
	)

operator<<() [58/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const SHOT352 &	p
	)

operator<<() [59/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const UniqueShapeContext1960 &	p
	)

operator<<() [60/69]

PCL_EXPORTS std::ostream& pcl::operator<<	(	std::ostream &	os,
		const VFHSignature308 &	p
	)

operator<<() [61/69]

std::ostream& pcl::operator<< ( std::ostream &  out, const PCLHeader &  h  )

inline

Definition at line 29 of file PCLHeader.h.

References pcl::PCLHeader::frame_id, pcl::PCLHeader::seq, and pcl::PCLHeader::stamp.

operator<<() [62/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::ModelCoefficients &  v  )

inline

Definition at line 27 of file ModelCoefficients.h.

operator<<() [63/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::PCLImage &  v  )

inline

Definition at line 32 of file PCLImage.h.

operator<<() [64/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::PCLPointCloud2 &  v  )

inline

Definition at line 121 of file PCLPointCloud2.h.

operator<<() [65/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::PCLPointField &  v  )

inline

Definition at line 40 of file PCLPointField.h.

operator<<() [66/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::PointIndices &  v  )

inline

Definition at line 26 of file PointIndices.h.

operator<<() [67/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::PolygonMesh &  v  )

inline

Definition at line 103 of file PolygonMesh.h.

operator<<() [68/69]

std::ostream& pcl::operator<< ( std::ostream &  s, const ::pcl::Vertices &  v  )

inline

Definition at line 29 of file Vertices.h.

operator<<() [69/69]

template<typename PointT >

std::ostream& pcl::operator<<	(	std::ostream &	s,
		const pcl::PointCloud< PointT > &	p
	)

Definition at line 904 of file point_cloud.h.

References pcl::PointCloud< PointT >::header, pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::is_dense, pcl::PointCloud< PointT >::sensor_orientation_, pcl::PointCloud< PointT >::sensor_origin_, pcl::PointCloud< PointT >::size(), and pcl::PointCloud< PointT >::width.

operator==()

bool pcl::operator== ( const PCLHeader &  lhs, const PCLHeader &  rhs  )

inline

Definition at line 37 of file PCLHeader.h.

References pcl::PCLHeader::frame_id, pcl::PCLHeader::seq, and pcl::PCLHeader::stamp.

parseTimestamp()

PCL_EXPORTS std::chrono::time_point<std::chrono::system_clock> pcl::parseTimestamp ( std::string  timestamp )

inline

Parses a iso timestring (see https://www.boost.org/doc/libs/1_81_0/doc/html/date_time/posix_time.html#ptime_to_string) and returns a timepoint.

Parameters

timestamp

as string formatted like boost iso date

Returns

std::chrono::time_point with system_clock

Definition at line 52 of file timestamp.h.

planeWithPlaneIntersection() [1/3]

template<typename Scalar >

bool pcl::planeWithPlaneIntersection	(	const Eigen::Matrix< Scalar, 4, 1 > &	plane_a,
		const Eigen::Matrix< Scalar, 4, 1 > &	plane_b,
		Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &	line,
		double	angular_tolerance = 0.1
	)

Determine the line of intersection of two non-parallel planes using lagrange multipliers.

Note

Described in: "Intersection of Two Planes, John Krumm, Microsoft Research, Redmond, WA, USA"

Parameters

[in]	plane_a	coefficients of plane A and plane B in the form ax + by + cz + d = 0
[in]	plane_b	coefficients of line where line.tail<3>() = direction vector and line.head<3>() the point on the line closest to (0, 0, 0)
[out]	line	the intersected line to be filled
[in]	angular_tolerance	tolerance in radians

Returns

true if succeeded/planes aren't parallel

Definition at line 79 of file intersections.hpp.

planeWithPlaneIntersection() [2/3]

bool pcl::planeWithPlaneIntersection ( const Eigen::Vector4d &  plane_a, const Eigen::Vector4d &  plane_b, Eigen::VectorXd &  line, double  angular_tolerance = 0.1  )

inline

Definition at line 105 of file intersections.h.

planeWithPlaneIntersection() [3/3]

bool pcl::planeWithPlaneIntersection ( const Eigen::Vector4f &  plane_a, const Eigen::Vector4f &  plane_b, Eigen::VectorXf &  line, double  angular_tolerance = 0.1  )

inline

Definition at line 96 of file intersections.h.

PointCloudDepthAndRGBtoXYZRGBA()

void pcl::PointCloudDepthAndRGBtoXYZRGBA ( const PointCloud< Intensity > &  depth, const PointCloud< RGB > &  image, const float &  focal, PointCloud< PointXYZRGBA > &  out  )

inline

Convert registered Depth image and RGB image to PointCloudXYZRGBA.

Parameters

[in]	depth	the input depth image as intensity points in float
[in]	image	the input RGB image
[in]	focal	the focal length
[out]	out	the output pointcloud

Definition at line 429 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::at(), pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudRGBtoI() [1/3]

void pcl::PointCloudRGBtoI ( const PointCloud< RGB > &  in, PointCloud< Intensity > &  out  )

inline

Convert a RGB point cloud to an Intensity.

Parameters

[in]	in	the input RGB point cloud
[out]	out	the output Intensity point cloud

Definition at line 301 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointRGBtoI(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudRGBtoI() [2/3]

void pcl::PointCloudRGBtoI ( const PointCloud< RGB > &  in, PointCloud< Intensity32u > &  out  )

inline

Convert a RGB point cloud to an Intensity.

Parameters

[in]	in	the input RGB point cloud
[out]	out	the output Intensity point cloud

Definition at line 337 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointRGBtoI(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudRGBtoI() [3/3]

void pcl::PointCloudRGBtoI ( const PointCloud< RGB > &  in, PointCloud< Intensity8u > &  out  )

inline

Convert a RGB point cloud to an Intensity.

Parameters

[in]	in	the input RGB point cloud
[out]	out	the output Intensity point cloud

Definition at line 319 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointRGBtoI(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudXYZHSVtoXYZRGB()

void pcl::PointCloudXYZHSVtoXYZRGB ( const PointCloud< PointXYZHSV > &  in, PointCloud< PointXYZRGB > &  out  )

inline

Convert a XYZHSV point cloud to a XYZRGB.

Parameters

[in]	in	the input XYZHSV point cloud
[out]	out	the output XYZRGB point cloud

Definition at line 373 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointXYZHSVtoXYZRGB(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudXYZRGBAtoXYZHSV()

void pcl::PointCloudXYZRGBAtoXYZHSV ( const PointCloud< PointXYZRGBA > &  in, PointCloud< PointXYZHSV > &  out  )

inline

Convert a XYZRGB point cloud to a XYZHSV.

Parameters

[in]	in	the input XYZRGB point cloud
[out]	out	the output XYZHSV point cloud

Definition at line 391 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointXYZRGBAtoXYZHSV(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudXYZRGBtoXYZHSV()

void pcl::PointCloudXYZRGBtoXYZHSV ( const PointCloud< PointXYZRGB > &  in, PointCloud< PointXYZHSV > &  out  )

inline

Convert a XYZRGB point cloud to a XYZHSV.

Parameters

[in]	in	the input XYZRGB point cloud
[out]	out	the output XYZHSV point cloud

Definition at line 355 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointXYZRGBtoXYZHSV(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointCloudXYZRGBtoXYZI()

void pcl::PointCloudXYZRGBtoXYZI ( const PointCloud< PointXYZRGB > &  in, PointCloud< PointXYZI > &  out  )

inline

Convert a XYZRGB point cloud to a XYZI.

Parameters

[in]	in	the input XYZRGB point cloud
[out]	out	the output XYZI point cloud

Definition at line 409 of file point_types_conversion.h.

References pcl::PointCloud< PointT >::height, PointXYZRGBtoXYZI(), pcl::PointCloud< PointT >::push_back(), and pcl::PointCloud< PointT >::width.

PointRGBtoI() [1/3]

void pcl::PointRGBtoI ( const RGB &  in, Intensity &  out  )

inline

Convert a RGB point type to a I.

Parameters

[in]	in	the input RGB point
[out]	out	the output Intensity point

Definition at line 72 of file point_types_conversion.h.

Referenced by PointCloudRGBtoI().

PointRGBtoI() [2/3]

void pcl::PointRGBtoI ( const RGB &  in, Intensity32u &  out  )

inline

Convert a RGB point type to a I.

Parameters

[in]	in	the input RGB point
[out]	out	the output Intensity point

Definition at line 95 of file point_types_conversion.h.

PointRGBtoI() [3/3]

void pcl::PointRGBtoI ( const RGB &  in, Intensity8u &  out  )

inline

Convert a RGB point type to a I.

Parameters

[in]	in	the input RGB point
[out]	out	the output Intensity point

Definition at line 83 of file point_types_conversion.h.

PointXYZHSVtoXYZRGB()

void pcl::PointXYZHSVtoXYZRGB ( const PointXYZHSV &  in, PointXYZRGB &  out  )

inline

Definition at line 233 of file point_types_conversion.h.

References pcl::_PointXYZHSV::h, pcl::_PointXYZHSV::s, and pcl::_PointXYZHSV::v.

Referenced by PointCloudXYZHSVtoXYZRGB().

PointXYZRGBAtoXYZHSV()

void pcl::PointXYZRGBAtoXYZHSV ( const PointXYZRGBA &  in, PointXYZHSV &  out  )

inline

Convert a XYZRGBA point type to a XYZHSV.

Parameters

[in]	in	the input XYZRGBA point
[out]	out	the output XYZHSV point

Todo:

include the A parameter but how?

Definition at line 196 of file point_types_conversion.h.

References pcl::_PointXYZHSV::h, pcl::_PointXYZHSV::s, and pcl::_PointXYZHSV::v.

Referenced by PointCloudXYZRGBAtoXYZHSV().

PointXYZRGBtoXYZHSV()

void pcl::PointXYZRGBtoXYZHSV ( const PointXYZRGB &  in, PointXYZHSV &  out  )

inline

Convert a XYZRGB point type to a XYZHSV.

Parameters

[in]	in	the input XYZRGB point
[out]	out	the output XYZHSV point

Definition at line 107 of file point_types_conversion.h.

References pcl::_PointXYZHSV::h, pcl::_PointXYZHSV::s, and pcl::_PointXYZHSV::v.

Referenced by PointCloudXYZRGBtoXYZHSV(), and seededHueSegmentation().

PointXYZRGBtoXYZI()

void pcl::PointXYZRGBtoXYZI ( const PointXYZRGB &  in, PointXYZI &  out  )

inline

Convert a XYZRGB point type to a XYZI.

Parameters

[in]	in	the input XYZRGB point
[out]	out	the output XYZI point

Definition at line 60 of file point_types_conversion.h.

References pcl::_PointXYZI::intensity.

Referenced by PointCloudXYZRGBtoXYZI().

PointXYZRGBtoXYZLAB()

template<typename PointT , traits::HasColor< PointT > = true>

void pcl::PointXYZRGBtoXYZLAB ( const PointT &  in, PointXYZLAB &  out  )

inline

Convert a XYZRGB-based point type to a XYZLAB.

Parameters

[in]	in	the input XYZRGB(XYZRGBA, XYZRGBL, etc.) point
[out]	out	the output XYZLAB point

Definition at line 145 of file point_types_conversion.h.

References pcl::_PointXYZLAB::a, B, pcl::_PointXYZLAB::b, and pcl::_PointXYZLAB::L.

projectPoint()

template<typename Point >

void pcl::projectPoint ( const Point &  p, const Eigen::Vector4f &  model_coefficients, Point &  q  )

inline

Project a point on a planar model given by a set of normalized coefficients.

Parameters

[in]	p	the input point to project
[in]	model_coefficients	the coefficients of the plane (a, b, c, d) that satisfy ax+by+cz+d=0
[out]	q	the resultant projected point

Definition at line 62 of file sac_model_plane.h.

Referenced by pcl::search::OrganizedNeighbor< PointT >::estimateProjectionMatrix().

radius_search()

template<class FlannIndex , class Query , class Indices , class Distances , class SearchParams >

int pcl::radius_search	(	const FlannIndex &	index,
		const Query &	query,
		Indices &	indices,
		Distances &	dists,
		float	radius,
		const SearchParams &	params
	)

Compatibility template function to allow use of various types of indices with FLANN.

Template is used for all params to not constrain any FLANN side capability

Parameters

[in,out]	index	A index searcher, of type ::flann::Index<Dist> or similar, where Dist is a template for computing distance between 2 points
[in]	query	A ::flann::Matrix<float> or compatible matrix representation of the query point
[out]	indices	Indices found in radius
[out]	dists	Computed distance matrix
[in]	radius	Threshold for consideration
[in]	params	Any parameters to pass to the radius_search call

Definition at line 360 of file kdtree_flann.hpp.

Referenced by pcl::KdTreeFLANN< PointT, Dist >::radiusSearch(), and pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch().

read() [1/2]

template<class Type >

void pcl::read	(	std::istream &	stream,
		Type &	value
	)

Function for reading data from a stream.

Definition at line 46 of file region_xy.h.

Referenced by pcl::RegionXY::deserialize(), pcl::DenseQuantizedSingleModTemplate::deserialize(), pcl::DenseQuantizedMultiModTemplate::deserialize(), pcl::QuantizedMultiModFeature::deserialize(), pcl::SparseQuantizedMultiModTemplate::deserialize(), pcl::poisson::SparseMatrix< T >::read(), pcl::poisson::Vector< T >::read(), pcl::FileReader::read(), pcl::PLYReader::read(), pcl::IFSReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), and read().

read() [2/2]

template<class Type >

void pcl::read	(	std::istream &	stream,
		Type *	value,
		int	nr_values
	)

Function for reading data arrays from a stream.

Definition at line 53 of file region_xy.h.

References read().

RGB2sRGB_LUT()

template<typename T , std::uint8_t bits = 8>

std::array<T, 1 << bits> pcl::RGB2sRGB_LUT ( )

inlinenoexcept

Returns a Look-Up Table useful in converting RGB to sRGB.

Template Parameters

T	floating point type with resultant value
bits	depth of RGB

Returns

1-D LUT for converting R, G or B into Rs, Gs or Bs

Remarks

sRGB was proposed by Stokes et al. as a uniform default color space for the internet M. Stokes, M. Anderson, S. Chandrasekar, and R. Motta: A standard default colorspace for the internet - sRGB (Nov 1996) IEC 61966-2.1 Default RGB Colour Space - sRGB (International Electrotechnical Commission, Geneva, Switzerland, 1999) www.srgb.com, www.color.org/srgb.html

Definition at line 102 of file colors.h.

setFieldValue()

template<typename PointT , typename ValT >

void pcl::setFieldValue ( PointT &  pt, std::size_t  field_offset, const ValT &  value  )

inline

Set the value at a specified field in a point.

Parameters

[out]	pt	the point to set the value to
[in]	field_offset	the offset of the field
[in]	value	the value to set

Definition at line 237 of file type_traits.h.

split()

template<typename SequenceSequenceT >

void pcl::split	(	SequenceSequenceT &	result,
		std::string const &	in,
		const char *const	delimiters
	)

Lightweight tokenization function This function can be used as a boost::split substitute.

When benchmarked against boost, this function will create much less allocations and hence it is much better suited for quick line tokenization.

Cool thing is this function will work with SequenceSequenceT = std::vector<std::string> and std::vector<std::string_view>

Definition at line 25 of file split.h.

squaredEuclideanDistance() [1/3]

template<>

float pcl::squaredEuclideanDistance ( const pcl::segmentation::grabcut::Color &  c1, const pcl::segmentation::grabcut::Color &  c2  )

inline

Definition at line 51 of file grabcut_segmentation.hpp.

References pcl::segmentation::grabcut::Color::b, pcl::segmentation::grabcut::Color::g, and pcl::segmentation::grabcut::Color::r.

squaredEuclideanDistance() [2/3]

template<typename PointType1 , typename PointType2 >

float pcl::squaredEuclideanDistance ( const PointType1 &  p1, const PointType2 &  p2  )

inline

Calculate the squared euclidean distance between the two given points.

Parameters

[in]	p1	the first point
[in]	p2	the second point

Definition at line 182 of file distances.h.

Referenced by pcl::filters::Pyramid< PointT >::compute(), pcl::GrabCut< PointT >::computeBetaNonOrganized(), pcl::GrabCut< PointT >::computeBetaOrganized(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::determineBaseMatches(), euclideanDistance(), pcl::RangeImage::getEuclideanDistanceSquared(), pcl::RangeImage::getImpactAngle(), pcl::RangeImageBorderExtractor::getNeighborDistanceChangeScore(), pcl::RangeImage::getSquaredDistanceOfNthNeighbor(), pcl::RangeImage::getSurfaceInformation(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::linkMatchWithBase(), pcl::SurfelSmoothing< PointT, PointNT >::smoothCloudIteration(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateMatch().

squaredEuclideanDistance() [3/3]

template<>

float pcl::squaredEuclideanDistance ( const PointXY &  p1, const PointXY &  p2  )

inline

Calculate the squared euclidean distance between the two given points.

Parameters

[in]	p1	the first point
[in]	p2	the second point

Definition at line 193 of file distances.h.

References pcl::PointXY::x, and pcl::PointXY::y.

threePlanesIntersection() [1/3]

template<typename Scalar >

bool pcl::threePlanesIntersection	(	const Eigen::Matrix< Scalar, 4, 1 > &	plane_a,
		const Eigen::Matrix< Scalar, 4, 1 > &	plane_b,
		const Eigen::Matrix< Scalar, 4, 1 > &	plane_c,
		Eigen::Matrix< Scalar, 3, 1 > &	intersection_point,
		double	determinant_tolerance = 1e-6
	)

Determine the point of intersection of three non-parallel planes by solving the equations.

Note

If using nearly parallel planes you can lower the determinant_tolerance value. This can lead to inconsistent results. If the three planes intersects in a line the point will be anywhere on the line.

Parameters

[in]	plane_a	are the coefficients of the first plane in the form ax + by + cz + d = 0
[in]	plane_b	are the coefficients of the second plane
[in]	plane_c	are the coefficients of the third plane
[in]	determinant_tolerance	is a limit to determine whether planes are parallel or not
[out]	intersection_point	the three coordinates x, y, z of the intersection point

Returns

true if succeeded/planes aren't parallel

Definition at line 127 of file intersections.hpp.

threePlanesIntersection() [2/3]

bool pcl::threePlanesIntersection ( const Eigen::Vector4d &  plane_a, const Eigen::Vector4d &  plane_b, const Eigen::Vector4d &  plane_c, Eigen::Vector3d &  intersection_point, double  determinant_tolerance = 1e-6  )

inline

Definition at line 144 of file intersections.h.

threePlanesIntersection() [3/3]

bool pcl::threePlanesIntersection ( const Eigen::Vector4f &  plane_a, const Eigen::Vector4f &  plane_b, const Eigen::Vector4f &  plane_c, Eigen::Vector3f &  intersection_point, double  determinant_tolerance = 1e-6  )

inline

Definition at line 133 of file intersections.h.

toPCLPointCloud2() [1/4]

template<typename CloudT >

void pcl::toPCLPointCloud2	(	const CloudT &	cloud,
		pcl::PCLImage &	msg
	)

Copy the RGB fields of a PointCloud into pcl::PCLImage format.

Parameters

[in]	cloud	the point cloud message
[out]	msg	the resultant pcl::PCLImage CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGBA>

Note

will throw std::runtime_error if there is a problem

Definition at line 442 of file conversions.h.

References pcl::PCLImage::data, pcl::PCLImage::encoding, pcl::PCLImage::header, pcl::PCLImage::height, pcl::PCLImage::step, and pcl::PCLImage::width.

toPCLPointCloud2() [2/4]

void pcl::toPCLPointCloud2 ( const pcl::PCLPointCloud2 &  cloud, pcl::PCLImage &  msg  )

inline

Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format.

Parameters

cloud	the point cloud message
msg	the resultant pcl::PCLImage will throw std::runtime_error if there is a problem

Definition at line 476 of file conversions.h.

References pcl::PCLImage::data, pcl::PCLPointCloud2::data, pcl::geometry::distance(), pcl::PCLImage::encoding, pcl::PCLPointCloud2::fields, pcl::PCLImage::header, pcl::PCLPointCloud2::header, pcl::PCLImage::height, pcl::PCLPointCloud2::height, pcl::PCLPointCloud2::point_step, pcl::PCLImage::step, pcl::PCLImage::width, and pcl::PCLPointCloud2::width.

toPCLPointCloud2() [3/4]

template<typename PointT >

void pcl::toPCLPointCloud2	(	const pcl::PointCloud< PointT > &	cloud,
		pcl::PCLPointCloud2 &	msg
	)

Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.

Parameters

[in]	cloud	the input pcl::PointCloud<T>
[out]	msg	the resultant PCLPointCloud2 binary blob

Definition at line 430 of file conversions.h.

References toPCLPointCloud2().

toPCLPointCloud2() [4/4]

template<typename PointT >

void pcl::toPCLPointCloud2	(	const pcl::PointCloud< PointT > &	cloud,
		pcl::PCLPointCloud2 &	msg,
		bool	padding
	)

Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.

Parameters

[in]	cloud	the input pcl::PointCloud<T>
[out]	msg	the resultant PCLPointCloud2 binary blob
[in]	padding	Many point types have padding to ensure alignment and SIMD compatibility. Setting this to true will copy the padding to the PCLPointCloud2 (the default in older PCL versions). Setting this to false will make the data blob in PCLPointCloud2 smaller, while still keeping all information (useful e.g. when sending msg over network or storing it). The amount of padding depends on the point type, and can in some cases be up to 50 percent.

Todo:

msg.is_bigendian = ?;

Definition at line 372 of file conversions.h.

References pcl::PCLPointCloud2::data, pcl::PointCloud< PointT >::data(), pcl::PCLPointCloud2::fields, pcl::PCLPointCloud2::header, pcl::PointCloud< PointT >::header, pcl::PCLPointCloud2::height, pcl::PointCloud< PointT >::height, pcl::PCLPointCloud2::is_dense, pcl::PointCloud< PointT >::is_dense, pcl::PCLPointCloud2::point_step, pcl::PCLPointCloud2::row_step, pcl::PointCloud< PointT >::size(), pcl::PCLPointCloud2::width, and pcl::PointCloud< PointT >::width.

Referenced by pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::computeTransformation(), pcl::JointIterativeClosestPoint< PointSource, PointTarget, Scalar >::computeTransformation(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::getMeshesFromTSDFVector(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::Poisson< PointNT >::performReconstruction(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::geometry::toFaceVertexMesh(), toPCLPointCloud2(), pcl::PLYWriter::write(), and pcl::FileWriter::write().

transformBetween2CoordinateSystems()

template<typename Scalar >

bool pcl::transformBetween2CoordinateSystems	(	const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >	from_line_x,
		const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >	from_line_y,
		const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >	to_line_x,
		const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >	to_line_y,
		Eigen::Transform< Scalar, 3, Eigen::Affine > &	transformation
	)

Compute the transformation between two coordinate systems.

Parameters

[in]	from_line_x	X axis from the origin coordinate system
[in]	from_line_y	Y axis from the origin coordinate system
[in]	to_line_x	X axis from the destination coordinate system
[in]	to_line_y	Y axis from the destination coordinate system
[out]	transformation	the transformation matrix to fill

Returns

true if transformation was filled, false otherwise.

Line must be filled in this form:
line[0-2] = Coordinate system origin coordinates
line[3-5] = Direction vector (norm doesn't matter)

Definition at line 864 of file eigen.hpp.

References checkCoordinateSystem().

transformLine()

template<typename Scalar >

bool pcl::transformLine	(	const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &	line_in,
		Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &	line_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transformation
	)

Transform a line using an affine matrix.

Parameters

[in]	line_in	the line to be transformed
[out]	line_out	the transformed line
[in]	transformation	the transformation matrix

Lines must be filled in this form:
line[0-2] = Origin coordinates of the vector
line[3-5] = Direction vector

Note

Can be used with line_in = line_out

Definition at line 746 of file eigen.hpp.

References transformPoint(), and transformVector().

transformPlane() [1/2]

template<typename Scalar >

void pcl::transformPlane	(	const Eigen::Matrix< Scalar, 4, 1 > &	plane_in,
		Eigen::Matrix< Scalar, 4, 1 > &	plane_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transformation
	)

Transform plane vectors using an affine matrix.

Parameters

[in]	plane_in	the plane coefficients to be transformed
[out]	plane_out	the transformed plane coefficients to fill
[in]	transformation	the transformation matrix

The plane vectors are filled in the form ax+by+cz+d=0 Can be used with non Hessian form planes coefficients Can be used with plane_in = plane_out

Definition at line 768 of file eigen.hpp.

Referenced by transformPlane().

transformPlane() [2/2]

template<typename Scalar >

void pcl::transformPlane	(	const pcl::ModelCoefficients::ConstPtr	plane_in,
		pcl::ModelCoefficients::Ptr	plane_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transformation
	)

Transform plane vectors using an affine matrix.

Parameters

[in]	plane_in	the plane coefficients to be transformed
[out]	plane_out	the transformed plane coefficients to fill
[in]	transformation	the transformation matrix

The plane vectors are filled in the form ax+by+cz+d=0 Can be used with non Hessian form planes coefficients Can be used with plane_in = plane_out

Warning

ModelCoefficients stores floats only !

Definition at line 785 of file eigen.hpp.

References transformPlane().

transformPoint() [1/2]

template<typename Scalar >

void pcl::transformPoint ( const Eigen::Matrix< Scalar, 3, 1 > &  point_in, Eigen::Matrix< Scalar, 3, 1 > &  point_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &  transformation  )

inline

Transform a point using an affine matrix.

Parameters

[in]	point_in	the vector to be transformed
[out]	point_out	the transformed vector
[in]	transformation	the transformation matrix

Note

Can be used with point_in = point_out

Definition at line 389 of file eigen.h.

Referenced by transformLine().

transformPoint() [2/2]

template<typename PointT >

PointT pcl::transformPoint ( const PointT &  point, const Eigen::Affine3f &  transform  )

inline

Definition at line 464 of file transforms.h.

transformPointCloud() [1/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 96 of file transforms.h.

transformPointCloud() [2/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 261 of file transforms.h.

transformPointCloud() [3/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 125 of file transforms.h.

References pcl::PointIndices::indices.

transformPointCloud() [4/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 290 of file transforms.h.

transformPointCloud() [5/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 68 of file transforms.h.

transformPointCloud() [6/7]

template<typename PointT >

void pcl::transformPointCloud	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 236 of file transforms.h.

transformPointCloud() [7/7]

template<typename PointT >

void pcl::transformPointCloud ( const pcl::PointCloud< PointT > &  cloud_in, pcl::PointCloud< PointT > &  cloud_out, const Eigen::Vector3f &  offset, const Eigen::Quaternionf &  rotation, bool  copy_all_fields = true  )

inline

Definition at line 403 of file transforms.h.

transformPointCloudWithNormals() [1/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 181 of file transforms.h.

transformPointCloudWithNormals() [2/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 345 of file transforms.h.

transformPointCloudWithNormals() [3/10]

template<typename PointT , typename Scalar >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const Indices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transform,
		bool	copy_all_fields = true
	)

Transform a point cloud and rotate its normals using an Eigen transform.

Parameters

[in]	cloud_in	the input point cloud
[in]	indices	the set of point indices to use from the input point cloud
[out]	cloud_out	the resultant output point cloud
[in]	transform	an affine transformation (typically a rigid transformation)
[in]	copy_all_fields	flag that controls whether the contents of the fields (other than x, y, z, normal_x, normal_y, normal_z) should be copied into the new transformed cloud

Definition at line 171 of file transforms.h.

transformPointCloudWithNormals() [4/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 211 of file transforms.h.

References pcl::PointIndices::indices.

transformPointCloudWithNormals() [5/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 377 of file transforms.h.

References pcl::PointIndices::indices.

transformPointCloudWithNormals() [6/10]

template<typename PointT , typename Scalar >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		const pcl::PointIndices &	indices,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transform,
		bool	copy_all_fields = true
	)

Transform a point cloud and rotate its normals using an Eigen transform.

Parameters

[in]	cloud_in	the input point cloud
[in]	indices	the set of point indices to use from the input point cloud
[out]	cloud_out	the resultant output point cloud
[in]	transform	an affine transformation (typically a rigid transformation)
[in]	copy_all_fields	flag that controls whether the contents of the fields (other than x, y, z, normal_x, normal_y, normal_z) should be copied into the new transformed cloud

Definition at line 200 of file transforms.h.

References pcl::PointIndices::indices.

transformPointCloudWithNormals() [7/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Affine3f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 153 of file transforms.h.

transformPointCloudWithNormals() [8/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Matrix4f &	transform,
		bool	copy_all_fields = true
	)

Definition at line 317 of file transforms.h.

transformPointCloudWithNormals() [9/10]

template<typename PointT , typename Scalar >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Transform< Scalar, 3, Eigen::Affine > &	transform,
		bool	copy_all_fields = true
	)

Transform a point cloud and rotate its normals using an Eigen transform.

Parameters

[in]	cloud_in	the input point cloud
[out]	cloud_out	the resultant output point cloud
[in]	transform	an affine transformation (typically a rigid transformation)
[in]	copy_all_fields	flag that controls whether the contents of the fields (other than x, y, z, normal_x, normal_y, normal_z) should be copied into the new transformed cloud

Note

Can be used with cloud_in equal to cloud_out

Definition at line 144 of file transforms.h.

transformPointCloudWithNormals() [10/10]

template<typename PointT >

void pcl::transformPointCloudWithNormals	(	const pcl::PointCloud< PointT > &	cloud_in,
		pcl::PointCloud< PointT > &	cloud_out,
		const Eigen::Vector3f &	offset,
		const Eigen::Quaternionf &	rotation,
		bool	copy_all_fields = true
	)

Definition at line 430 of file transforms.h.

transformPointWithNormal()

template<typename PointT >

PointT pcl::transformPointWithNormal ( const PointT &  point, const Eigen::Affine3f &  transform  )

inline

Definition at line 481 of file transforms.h.

transformVector()

template<typename Scalar >

void pcl::transformVector ( const Eigen::Matrix< Scalar, 3, 1 > &  vector_in, Eigen::Matrix< Scalar, 3, 1 > &  vector_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &  transformation  )

inline

Transform a vector using an affine matrix.

Parameters

[in]	vector_in	the vector to be transformed
[out]	vector_out	the transformed vector
[in]	transformation	the transformation matrix

Note

Can be used with vector_in = vector_out

Definition at line 406 of file eigen.h.

Referenced by transformLine().

umeyama()

template<typename Derived , typename OtherDerived >

Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type pcl::umeyama	(	const Eigen::MatrixBase< Derived > &	src,
		const Eigen::MatrixBase< OtherDerived > &	dst,
		bool	with_scaling = false
	)

Returns the transformation between two point sets.

The algorithm is based on: "Least-squares estimation of transformation parameters between two point patterns", Shinji Umeyama, PAMI 1991, DOI: 10.1109/34.88573

It estimates parameters and such that

is minimized.

The algorithm is based on the analysis of the covariance matrix of the input point sets and where is corresponding to the dimension (which is typically small). The analysis is involving the SVD having a complexity of though the actual computational effort lies in the covariance matrix computation which has an asymptotic lower bound of when the input point sets have dimension .

Parameters

[in]	src	Source points
[in]	dst	Destination points .
[in]	with_scaling	Sets when false is passed. (default: false)

Returns

The homogeneous transformation

minimizing the resudiual above. This transformation is always returned as an Eigen::Matrix.

Definition at line 670 of file eigen.hpp.

Referenced by pcl::SampleConsensusModelRegistration< PointT >::estimateRigidTransformationSVD().

write() [1/2]

template<class Type >

void pcl::write	(	std::ostream &	stream,
		Type *	value,
		int	nr_values
	)

Function for writing data arrays to a stream.

Definition at line 70 of file region_xy.h.

References write().

write() [2/2]

template<class Type >

void pcl::write	(	std::ostream &	stream,
		Type	value
	)

Function for writing data to a stream.

Definition at line 63 of file region_xy.h.

Referenced by pcl::DenseQuantizedSingleModTemplate::serialize(), pcl::DenseQuantizedMultiModTemplate::serialize(), pcl::RegionXY::serialize(), pcl::QuantizedMultiModFeature::serialize(), pcl::SparseQuantizedMultiModTemplate::serialize(), pcl::io::LZFImageWriter::write(), pcl::poisson::SparseMatrix< T >::write(), pcl::poisson::Vector< T >::write(), pcl::PLYWriter::write(), pcl::FileWriter::write(), pcl::PCDWriter::write(), pcl::IFSWriter::write(), and write().

XYZ2LAB_LUT()

template<typename T , std::size_t discretizations = 4000>

const std::array<T, discretizations>& pcl::XYZ2LAB_LUT ( )

inlinenoexcept

Returns a Look-Up Table useful in converting scaled CIE XYZ into CIE L*a*b*.

The function assumes that the XYZ values are

• not normalized using reference illuminant
• scaled such that reference illuminant has Xn = Yn = Zn = discretizations

  Template Parameters

  T	floating point type with resultant value
  discretizations	number of levels for the LUT

  Returns

  1-D LUT with results of f(X/Xn)

  Note

  This function doesn't convert from CIE XYZ to CIE L*a*b*. The actual conversion is as follows: L* = 116 * [f(Y/Yn) - 16/116] a* = 500 * [f(X/Xn) - f(Y/Yn)] b* = 200 * [f(Y/Yn) - f(Z/Zn)] Where, Xn, Yn and Zn are values of the reference illuminant (at prescribed angle) f is appropriate function such that L* = 100, a* = b* = 0 for white color Reference: Billmeyer and Saltzman’s Principles of Color Technology

Definition at line 148 of file colors.h.

Variable Documentation

edgeTable

const unsigned int pcl::edgeTable[256]

Definition at line 59 of file marching_cubes.h.

Referenced by pcl::MarchingCubes< PointNT >::createSurface().

I_SHIFT_EDGE

const int pcl::I_SHIFT_EDGE[3][2]

Initial value:

= {
    {0,1}, {1,3}, {1,2}
  }

Definition at line 60 of file grid_projection.h.

Referenced by pcl::GridProjection< PointNT >::createSurfaceForCell().

I_SHIFT_EP

const int pcl::I_SHIFT_EP[12][2]

Initial value:

= {
    {0, 4}, {1, 5}, {2, 6}, {3, 7}, 
    {0, 1}, {1, 2}, {2, 3}, {3, 0},
    {4, 5}, {5, 6}, {6, 7}, {7, 4}
  }

The 12 edges of a cell.

Definition at line 50 of file grid_projection.h.

I_SHIFT_PT

const int pcl::I_SHIFT_PT[4]

Initial value:

= {
    0, 4, 5, 7
  }

Definition at line 56 of file grid_projection.h.

Referenced by pcl::GridProjection< PointNT >::createSurfaceForCell().

is_invocable_r_v

template<typename R , typename F , typename... Args>

constexpr bool pcl::is_invocable_r_v

constexpr

Initial value:

=
      std::is_constructible<std::function<R(Args...)>,
                            std::reference_wrapper<std::remove_reference_t<F>>>::value

Definition at line 285 of file type_traits.h.

is_invocable_v

template<typename F , typename... Args>

constexpr bool pcl::is_invocable_v

constexpr

Initial value:

=
      std::is_constructible<std::function<void(Args...)>,
                            std::reference_wrapper<std::remove_reference_t<F>>>::value

Todo:

: Remove in C++17

Definition at line 280 of file type_traits.h.

SAC_LMEDS

constexpr int pcl::SAC_LMEDS = 1

constexpr

Definition at line 46 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_MLESAC

constexpr int pcl::SAC_MLESAC = 5

constexpr

Definition at line 50 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_MSAC

constexpr int pcl::SAC_MSAC = 2

constexpr

Definition at line 47 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_PROSAC

constexpr int pcl::SAC_PROSAC = 6

constexpr

Definition at line 51 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_RANSAC

constexpr int pcl::SAC_RANSAC = 0

constexpr

Definition at line 45 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_RMSAC

constexpr int pcl::SAC_RMSAC = 4

constexpr

Definition at line 49 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

SAC_RRANSAC

constexpr int pcl::SAC_RRANSAC = 3

constexpr

Definition at line 48 of file method_types.h.

Referenced by pcl::SACSegmentation< PointT >::initSAC().

triTable

const int pcl::triTable[256][16]

Definition at line 93 of file marching_cubes.h.

Referenced by pcl::MarchingCubes< PointNT >::createSurface().

UNAVAILABLE

constexpr index_t pcl::UNAVAILABLE = static_cast<index_t>(-1)

staticconstexpr

Definition at line 62 of file pcl_base.h.

Referenced by pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PointPickingEvent::getPointIndices(), pcl::visualization::PointPickingEvent::getPoints(), pcl::GrabCut< PointT >::initGraph(), pcl::visualization::PointCloudGeometryHandlerCustom< PointT >::PointCloudGeometryHandlerCustom(), pcl::visualization::PointCloudGeometryHandlerSurfaceNormal< PointT >::PointCloudGeometryHandlerSurfaceNormal(), and pcl::visualization::PointCloudGeometryHandlerXYZ< PointT >::PointCloudGeometryHandlerXYZ().