Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation. More...

#include <pcl/features/linear_least_squares_normal.h>

Inheritance diagram for pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >:

Collaboration diagram for pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >:

Public Types
using	Ptr = shared_ptr< LinearLeastSquaresNormalEstimation< PointInT, PointOutT > >

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

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

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

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
	LinearLeastSquaresNormalEstimation ()
	Constructor. More...

	~LinearLeastSquaresNormalEstimation () override
	Destructor. More...

void	computePointNormal (const int pos_x, const int pos_y, PointOutT &normal)
	Computes the normal at the specified position. More...

void	setNormalSmoothingSize (float normal_smoothing_size)
	Set the normal smoothing size. More...

void	setDepthDependentSmoothing (bool use_depth_dependent_smoothing)
	Set whether to use depth depending smoothing or not. More...

void	setMaxDepthChangeFactor (float max_depth_change_factor)
	The depth change threshold for computing object borders. More...

void	setInputCloud (const typename PointCloudIn::ConstPtr &cloud) override
	Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method) 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 Member Functions
void	computeFeature (PointCloudOut &output) override
	Computes the normal for the complete cloud. 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	initCompute ()
	This method should get called before starting the actual computation. 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...

Additional Inherited Members
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...

Detailed Description

template<typename PointInT, typename PointOutT>
class pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >

Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation.

Author: Stefan Holzer, Cedric Cagniart

Definition at line 49 of file linear_least_squares_normal.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointInT , typename PointOutT >

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

Definition at line 53 of file linear_least_squares_normal.h.

◆ PointCloudIn

template<typename PointInT , typename PointOutT >

using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn

Definition at line 54 of file linear_least_squares_normal.h.

◆ PointCloudOut

template<typename PointInT , typename PointOutT >

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

Definition at line 55 of file linear_least_squares_normal.h.

◆ Ptr

template<typename PointInT , typename PointOutT >

using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::Ptr = shared_ptr<LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >

Definition at line 52 of file linear_least_squares_normal.h.

Constructor & Destructor Documentation

◆ LinearLeastSquaresNormalEstimation()

template<typename PointInT , typename PointOutT >

pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::LinearLeastSquaresNormalEstimation ( )

inline

Constructor.

Definition at line 62 of file linear_least_squares_normal.h.

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

◆ ~LinearLeastSquaresNormalEstimation()

template<typename PointInT , typename PointOutT >

pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::~LinearLeastSquaresNormalEstimation ( )

overridedefault

Destructor.

Member Function Documentation

◆ computeFeature()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computeFeature ( PointCloudOut & output )

overrideprotectedvirtual

Computes the normal for the complete cloud.

Parameters

[out] output the resultant normals

Implements pcl::Feature< PointInT, PointOutT >.

Definition at line 153 of file linear_least_squares_normal.hpp.

◆ computePointNormal()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computePointNormal	(	const int	pos_x,
		const int	pos_y,
		PointOutT &	normal
	)

Computes the normal at the specified position.

Parameters

[in]	pos_x	x position (pixel)
[in]	pos_y	y position (pixel)
[out]	normal	the output estimated normal

Definition at line 51 of file linear_least_squares_normal.hpp.

◆ setDepthDependentSmoothing()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setDepthDependentSmoothing ( bool use_depth_dependent_smoothing )

inline

Set whether to use depth depending smoothing or not.

Parameters

[in] use_depth_dependent_smoothing decides whether the smoothing is depth dependent

Definition at line 94 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setInputCloud()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setInputCloud ( const typename PointCloudIn::ConstPtr & cloud )

inlineoverride

Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)

Parameters

[in] cloud the const boost shared pointer to a PointCloud message

Definition at line 113 of file linear_least_squares_normal.h.

References pcl::PCLBase< PointInT >::input_.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setMaxDepthChangeFactor()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setMaxDepthChangeFactor ( float max_depth_change_factor )

inline

The depth change threshold for computing object borders.

Parameters

[in] max_depth_change_factor the depth change threshold for computing object borders based on depth changes

Definition at line 104 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setNormalSmoothingSize()

template<typename PointInT , typename PointOutT >

void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setNormalSmoothingSize ( float normal_smoothing_size )

inline

Set the normal smoothing size.

Parameters

[in] normal_smoothing_size factor which influences the size of the area used to smooth normals (depth dependent if useDepthDependentSmoothing is true)

Definition at line 85 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

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

pcl/features/linear_least_squares_normal.h
pcl/features/impl/linear_least_squares_normal.hpp

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

template<typename PointInT, typename PointOutT> class pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >

Member Typedef Documentation

◆ ConstPtr

◆ PointCloudIn

◆ PointCloudOut

◆ Ptr

Constructor & Destructor Documentation

◆ LinearLeastSquaresNormalEstimation()

◆ ~LinearLeastSquaresNormalEstimation()

Member Function Documentation

◆ computeFeature()

◆ computePointNormal()

◆ setDepthDependentSmoothing()

◆ setInputCloud()

◆ setMaxDepthChangeFactor()

◆ setNormalSmoothingSize()

template<typename PointInT, typename PointOutT>
class pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >