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...

#include <pcl/features/our_cvfh.h>

Inheritance diagram for pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >:

Collaboration diagram for pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >:

Public Types
using	Ptr = shared_ptr< OURCVFHEstimation< PointInT, PointNT, PointOutT > >

using	ConstPtr = shared_ptr< const OURCVFHEstimation< PointInT, PointNT, PointOutT > >

using	PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut

using	KdTreePtr = typename pcl::search::Search< PointNormal >::Ptr

using	PointInTPtr = typename pcl::PointCloud< PointInT >::Ptr

Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
using	PointCloudN = pcl::PointCloud< PointNT >

using	PointCloudNPtr = typename PointCloudN::Ptr

using	PointCloudNConstPtr = typename PointCloudN::ConstPtr

using	Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > >

using	ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > >

Public Types inherited from pcl::Feature< PointInT, PointOutT >
using	BaseClass = PCLBase< PointInT >

using	Ptr = shared_ptr< Feature< PointInT, PointOutT > >

using	ConstPtr = shared_ptr< const Feature< PointInT, PointOutT > >

using	KdTree = pcl::search::Search< PointInT >

using	KdTreePtr = typename KdTree::Ptr

using	PointCloudIn = pcl::PointCloud< PointInT >

using	PointCloudInPtr = typename PointCloudIn::Ptr

using	PointCloudInConstPtr = typename PointCloudIn::ConstPtr

using	PointCloudOut = pcl::PointCloud< PointOutT >

using	SearchMethod = std::function< int(std::size_t, double, pcl::Indices &, std::vector< float > &)>

using	SearchMethodSurface = std::function< int(const PointCloudIn &cloud, std::size_t index, double, pcl::Indices &, std::vector< float > &)>

Public Types inherited from pcl::PCLBase< PointInT >
using	PointCloud = pcl::PointCloud< PointInT >

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

Public Member Functions
	OURCVFHEstimation ()
	Empty constructor. More...

Eigen::Matrix4f	createTransFromAxes (Eigen::Vector3f &evx, Eigen::Vector3f &evy, Eigen::Vector3f &evz, Eigen::Affine3f &transformPC, Eigen::Matrix4f &center_mat)
	Creates an affine transformation from the RF axes. More...

void	computeRFAndShapeDistribution (PointInTPtr &processed, PointCloudOut &output, std::vector< pcl::PointIndices > &cluster_indices)
	Computes SGURF and the shape distribution based on the selected SGURF. More...

bool	sgurf (Eigen::Vector3f &centroid, Eigen::Vector3f &normal_centroid, PointInTPtr &processed, std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &transformations, PointInTPtr &grid, pcl::PointIndices &indices)
	Computes SGURF. More...

void	filterNormalsWithHighCurvature (const pcl::PointCloud< PointNT > &cloud, pcl::Indices &indices_to_use, pcl::Indices &indices_out, pcl::Indices &indices_in, float threshold)
	Removes normals with high curvature caused by real edges or noisy data. More...

void	setViewPoint (float vpx, float vpy, float vpz)
	Set the viewpoint. More...

void	setRadiusNormals (float radius_normals)
	Set the radius used to compute normals. More...

void	getViewPoint (float &vpx, float &vpy, float &vpz)
	Get the viewpoint. More...

void	getCentroidClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &centroids)
	Get the centroids used to compute different CVFH descriptors. More...

void	getCentroidNormalClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &centroids)
	Get the normal centroids used to compute different CVFH descriptors. More...

void	setClusterTolerance (float d)
	Sets max. More...

void	setEPSAngleThreshold (float d)
	Sets max. More...

void	setCurvatureThreshold (float d)
	Sets curvature threshold for removing normals. More...

void	setMinPoints (std::size_t min)
	Set minimum amount of points for a cluster to be considered. More...

void	setNormalizeBins (bool normalize)
	Sets whether the signatures should be normalized or not. More...

void	getClusterIndices (std::vector< pcl::PointIndices > &indices)
	Gets the indices of the original point cloud used to compute the signatures. More...

void	getClusterAxes (std::vector< short > &cluster_axes)
	Gets the number of non-disambiguable axes that correspond to each centroid. More...

void	setRefineClusters (float rc)
	Sets the refinement factor for the clusters. More...

void	getTransforms (std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &trans)
	Returns the transformations aligning the point cloud to the corresponding SGURF. More...

void	getValidTransformsVec (std::vector< bool > &valid)
	Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a valid SGURF. More...

void	setAxisRatio (float f)
	Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible. More...

void	setMinAxisValue (float f)
	Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition is difficult. More...

void	compute (PointCloudOut &output)
	Overloaded computed method from pcl::Feature. More...

Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
	FeatureFromNormals ()
	Empty constructor. More...

void	setInputNormals (const PointCloudNConstPtr &normals)
	Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More...

PointCloudNConstPtr	getInputNormals () const
	Get a pointer to the normals of the input XYZ point cloud dataset. More...

Public Member Functions inherited from pcl::Feature< PointInT, PointOutT >
	Feature ()
	Empty constructor. More...

void	setSearchSurface (const PointCloudInConstPtr &cloud)
	Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More...

PointCloudInConstPtr	getSearchSurface () const
	Get a pointer to the surface point cloud dataset. More...

void	setSearchMethod (const KdTreePtr &tree)
	Provide a pointer to the search object. More...

KdTreePtr	getSearchMethod () const
	Get a pointer to the search method used. More...

double	getSearchParameter () const
	Get the internal search parameter. More...

void	setKSearch (int k)
	Set the number of k nearest neighbors to use for the feature estimation. More...

int	getKSearch () const
	get the number of k nearest neighbors used for the feature estimation. More...

void	setRadiusSearch (double radius)
	Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More...

double	getRadiusSearch () const
	Get the sphere radius used for determining the neighbors. More...

void	compute (PointCloudOut &output)
	Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More...

Public Member Functions inherited from pcl::PCLBase< PointInT >
	PCLBase ()
	Empty constructor. More...

	PCLBase (const PCLBase &base)
	Copy constructor. More...

virtual	~PCLBase ()=default
	Destructor. More...

virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset. More...

PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset. More...

virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...

virtual void	setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud. More...

IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used. More...

IndicesConstPtr const	getIndices () const
	Get a pointer to the vector of indices used. More...

const PointInT &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code. More...

Protected Attributes
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > >	centroids_dominant_orientations_
	Centroids that were used to compute different OUR-CVFH descriptors. More...

std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > >	dominant_normals_
	Normal centroids that were used to compute different OUR-CVFH descriptors. More...

std::vector< pcl::PointIndices >	clusters_
	Indices to the points representing the stable clusters. More...

std::vector< short >	cluster_axes_
	Mapping from clusters to OUR-CVFH descriptors. More...

Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
PointCloudNConstPtr	normals_
	A pointer to the input dataset that contains the point normals of the XYZ dataset. More...

Protected Attributes inherited from pcl::Feature< PointInT, PointOutT >
std::string	feature_name_
	The feature name. More...

SearchMethodSurface	search_method_surface_
	The search method template for points. More...

PointCloudInConstPtr	surface_
	An input point cloud describing the surface that is to be used for nearest neighbors estimation. More...

KdTreePtr	tree_
	A pointer to the spatial search object. More...

double	search_parameter_
	The actual search parameter (from either search_radius_ or k_). More...

double	search_radius_
	The nearest neighbors search radius for each point. More...

int	k_
	The number of K nearest neighbors to use for each point. More...

bool	fake_surface_
	If no surface is given, we use the input PointCloud as the surface. More...

Protected Attributes inherited from pcl::PCLBase< PointInT >
PointCloudConstPtr	input_
	The input point cloud dataset. More...

IndicesPtr	indices_
	A pointer to the vector of point indices to use. More...

bool	use_indices_
	Set to true if point indices are used. More...

bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...

Additional Inherited Members
Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
virtual bool	initCompute ()
	This method should get called before starting the actual computation. More...

Protected Member Functions inherited from pcl::Feature< PointInT, PointOutT >
const std::string &	getClassName () const
	Get a string representation of the name of this class. More...

virtual bool	deinitCompute ()
	This method should get called after ending the actual computation. More...

int	searchForNeighbors (std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const
	Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More...

int	searchForNeighbors (const PointCloudIn &cloud, std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const
	Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More...

Protected Member Functions inherited from pcl::PCLBase< PointInT >
bool	initCompute ()
	This method should get called before starting the actual computation. More...

bool	deinitCompute ()
	This method should get called after finishing the actual computation. More...

Detailed Description

template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308>
class pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >

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:

OUR-CVFH – Oriented, Unique and Repeatable Clustered Viewpoint Feature Histogram for Object Recognition and 6DOF Pose Estimation A. Aldoma, F. Tombari, R.B. Rusu and M. Vincze DAGM-OAGM 2012 Graz, Austria The suggested PointOutT is pcl::VFHSignature308.

Author: Aitor Aldoma

Definition at line 59 of file our_cvfh.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const OURCVFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 63 of file our_cvfh.h.

◆ KdTreePtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::KdTreePtr = typename pcl::search::Search<PointNormal>::Ptr

Definition at line 73 of file our_cvfh.h.

◆ PointCloudOut

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 72 of file our_cvfh.h.

◆ PointInTPtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointInTPtr = typename pcl::PointCloud<PointInT>::Ptr

Definition at line 74 of file our_cvfh.h.

◆ Ptr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<OURCVFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 62 of file our_cvfh.h.

Constructor & Destructor Documentation

◆ OURCVFHEstimation()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::OURCVFHEstimation ( )

inline

Empty constructor.

Definition at line 76 of file our_cvfh.h.

References pcl::Feature< PointInT, PointOutT >::feature_name_, pcl::Feature< PointInT, PointOutT >::k_, and pcl::Feature< PointInT, PointOutT >::search_radius_.

Member Function Documentation

◆ compute()

template<typename PointInT , typename PointNT , typename PointOutT >

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::compute ( PointCloudOut & output )

Overloaded computed method from pcl::Feature.

Parameters

[out] output the resultant point cloud model dataset containing the estimated features

Definition at line 53 of file our_cvfh.hpp.

References pcl::PointCloud< PointT >::clear(), pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::resize(), and pcl::PointCloud< PointT >::width.

◆ computeRFAndShapeDistribution()

template<typename PointInT , typename PointNT , typename PointOutT >

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution	(	PointInTPtr &	processed,
		PointCloudOut &	output,
		std::vector< pcl::PointIndices > &	cluster_indices
	)

Computes SGURF and the shape distribution based on the selected SGURF.

Parameters

[in]	processed	the input cloud
[out]	output	the resulting signature
[in]	cluster_indices	the indices of the stable cluster

Definition at line 383 of file our_cvfh.hpp.

References pcl::PointCloud< PointT >::clear(), pcl::PointCloud< PointT >::empty(), pcl::getMaxDistance(), pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::push_back(), pcl::PointCloud< PointT >::resize(), pcl::PointCloud< PointT >::size(), pcl::transformPointCloud(), and pcl::PointCloud< PointT >::width.

◆ createTransFromAxes()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

Eigen::Matrix4f pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::createTransFromAxes	(	Eigen::Vector3f &	evx,
		Eigen::Vector3f &	evy,
		Eigen::Vector3f &	evz,
		Eigen::Affine3f &	transformPC,
		Eigen::Matrix4f &	center_mat
	)

inline

Creates an affine transformation from the RF axes.

Parameters

[in]	evx	the x-axis
[in]	evy	the y-axis
[in]	evz	the z-axis
[out]	transformPC	the resulting transformation
[in]	center_mat	4x4 matrix concatenated to the resulting transformation

Definition at line 97 of file our_cvfh.h.

◆ filterNormalsWithHighCurvature()

template<typename PointInT , typename PointNT , typename PointOutT >

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature	(	const pcl::PointCloud< PointNT > &	cloud,
		pcl::Indices &	indices_to_use,
		pcl::Indices &	indices_out,
		pcl::Indices &	indices_in,
		float	threshold
	)

Removes normals with high curvature caused by real edges or noisy data.

Parameters

[in]	cloud	pointcloud to be filtered
[in]	indices_to_use
[out]	indices_out	the indices of the points with higher curvature than threshold
[out]	indices_in	the indices of the remaining points after filtering
[in]	threshold	threshold value for curvature

Definition at line 170 of file our_cvfh.hpp.

References pcl::PointCloud< PointT >::size().

◆ getCentroidClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidClusters ( std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > & centroids )

inline

Get the centroids used to compute different CVFH descriptors.

Parameters

[out] centroids vector to hold the centroids

Definition at line 191 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_.

◆ getCentroidNormalClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidNormalClusters ( std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > & centroids )

inline

Get the normal centroids used to compute different CVFH descriptors.

Parameters

[out] centroids vector to hold the normal centroids

Definition at line 201 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_.

◆ getClusterAxes()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterAxes ( std::vector< short > & cluster_axes )

inline

Gets the number of non-disambiguable axes that correspond to each centroid.

Parameters

[out] cluster_axes vector mapping each centroid to the number of signatures

Definition at line 266 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::cluster_axes_.

◆ getClusterIndices()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterIndices ( std::vector< pcl::PointIndices > & indices )

inline

Gets the indices of the original point cloud used to compute the signatures.

Parameters

[out] indices vector of point indices

Definition at line 257 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::clusters_.

◆ getTransforms()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getTransforms ( std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > & trans )

inline

Returns the transformations aligning the point cloud to the corresponding SGURF.

Parameters

[out] trans vector of transformations

Definition at line 284 of file our_cvfh.h.

◆ getValidTransformsVec()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getValidTransformsVec ( std::vector< bool > & valid )

inline

Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a valid SGURF.

Parameters

[out] valid vector of booleans

Definition at line 294 of file our_cvfh.h.

◆ getViewPoint()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getViewPoint	(	float &	vpx,
		float &	vpy,
		float &	vpz
	)

inline

Get the viewpoint.

Parameters

[out]	vpx	the X coordinate of the viewpoint
[out]	vpy	the Y coordinate of the viewpoint
[out]	vpz	the Z coordinate of the viewpoint

Definition at line 180 of file our_cvfh.h.

◆ setAxisRatio()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setAxisRatio ( float f )

inline

Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible.

Parameters

[in] f the ratio between axes

Definition at line 303 of file our_cvfh.h.

◆ setClusterTolerance()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setClusterTolerance ( float d )

inline

Sets max.

Euclidean distance between points to be added to the cluster

Parameters

[in] d the maximum Euclidean distance

Definition at line 212 of file our_cvfh.h.

◆ setCurvatureThreshold()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setCurvatureThreshold ( float d )

inline

Sets curvature threshold for removing normals.

Parameters

[in] d the curvature threshold

Definition at line 230 of file our_cvfh.h.

◆ setEPSAngleThreshold()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setEPSAngleThreshold ( float d )

inline

Sets max.

deviation of the normals between two points so they can be clustered together

Parameters

[in] d the maximum deviation

Definition at line 221 of file our_cvfh.h.

◆ setMinAxisValue()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setMinAxisValue ( float f )

inline

Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition is difficult.

Parameters

[in] f the min axis value

Definition at line 312 of file our_cvfh.h.

◆ setMinPoints()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setMinPoints ( std::size_t min )

inline

Set minimum amount of points for a cluster to be considered.

Parameters

[in] min the minimum amount of points to be set

Definition at line 239 of file our_cvfh.h.

◆ setNormalizeBins()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setNormalizeBins ( bool normalize )

inline

Sets whether the signatures should be normalized or not.

Parameters

[in] normalize true if normalization is required, false otherwise

Definition at line 248 of file our_cvfh.h.

◆ setRadiusNormals()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setRadiusNormals ( float radius_normals )

inline

Set the radius used to compute normals.

Parameters

[in] radius_normals the radius

Definition at line 169 of file our_cvfh.h.

◆ setRefineClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setRefineClusters ( float rc )

inline

Sets the refinement factor for the clusters.

Parameters

[in] rc the factor used to decide if a point is used to estimate a stable cluster

Definition at line 275 of file our_cvfh.h.

◆ setViewPoint()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setViewPoint	(	float	vpx,
		float	vpy,
		float	vpz
	)

inline

Set the viewpoint.

Parameters

[in]	vpx	the X coordinate of the viewpoint
[in]	vpy	the Y coordinate of the viewpoint
[in]	vpz	the Z coordinate of the viewpoint

Definition at line 158 of file our_cvfh.h.

◆ sgurf()

template<typename PointInT , typename PointNT , typename PointOutT >

bool pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::sgurf	(	Eigen::Vector3f &	centroid,
		Eigen::Vector3f &	normal_centroid,
		PointInTPtr &	processed,
		std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &	transformations,
		PointInTPtr &	grid,
		pcl::PointIndices &	indices
	)

Computes SGURF.

Parameters

[in]	centroid	the centroid of the cluster
[in]	normal_centroid	the average of the normals
[in]	processed	the input cloud
[out]	transformations	the transformations aligning the cloud to the SGURF axes
[out]	grid	the cloud transformed internally
[in]	indices	the indices of the stable cluster

Definition at line 200 of file our_cvfh.hpp.

References pcl::demeanPointCloud(), pcl::getMaxDistance(), pcl::PointIndices::indices, and pcl::transformPointCloud().

Member Data Documentation

◆ centroids_dominant_orientations_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_

protected

Centroids that were used to compute different OUR-CVFH descriptors.

Definition at line 394 of file our_cvfh.h.

Referenced by pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidClusters().

◆ cluster_axes_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

std::vector<short> pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::cluster_axes_

protected

Mapping from clusters to OUR-CVFH descriptors.

Definition at line 400 of file our_cvfh.h.

Referenced by pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterAxes().

◆ clusters_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

std::vector<pcl::PointIndices> pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::clusters_

protected

Indices to the points representing the stable clusters.

Definition at line 398 of file our_cvfh.h.

Referenced by pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterIndices().

◆ dominant_normals_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>

std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_

protected

Normal centroids that were used to compute different OUR-CVFH descriptors.

Definition at line 396 of file our_cvfh.h.

Referenced by pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidNormalClusters().

The documentation for this class was generated from the following files:

pcl/features/our_cvfh.h
pcl/features/impl/our_cvfh.hpp

Public Types

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308> class pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >

Member Typedef Documentation

◆ ConstPtr

◆ KdTreePtr

◆ PointCloudOut

◆ PointInTPtr

◆ Ptr

Constructor & Destructor Documentation

◆ OURCVFHEstimation()

Member Function Documentation

◆ compute()

◆ computeRFAndShapeDistribution()

◆ createTransFromAxes()

◆ filterNormalsWithHighCurvature()

◆ getCentroidClusters()

◆ getCentroidNormalClusters()

◆ getClusterAxes()

◆ getClusterIndices()

◆ getTransforms()

◆ getValidTransformsVec()

◆ getViewPoint()

◆ setAxisRatio()

◆ setClusterTolerance()

◆ setCurvatureThreshold()

◆ setEPSAngleThreshold()

◆ setMinAxisValue()

◆ setMinPoints()

◆ setNormalizeBins()

◆ setRadiusNormals()

◆ setRefineClusters()

◆ setViewPoint()

◆ sgurf()

Member Data Documentation

◆ centroids_dominant_orientations_

◆ cluster_axes_

◆ clusters_

◆ dominant_normals_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308>
class pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >