PointCloudLibrary

CorrespondenceEstimationBackprojection computes correspondences as points in the target cloud which have minimum More...

#include <pcl/registration/correspondence_estimation_backprojection.h>

Public Types
using	Ptr = shared_ptr< CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar > >

using	ConstPtr = shared_ptr< const CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar > >

using	KdTree = pcl::search::KdTree< PointTarget >

using	KdTreePtr = typename KdTree::Ptr

using	PointCloudSource = pcl::PointCloud< PointSource >

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = pcl::PointCloud< PointTarget >

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointCloudNormals = pcl::PointCloud< NormalT >

using	NormalsPtr = typename PointCloudNormals::Ptr

using	NormalsConstPtr = typename PointCloudNormals::ConstPtr

Public Types inherited from pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >
using	Ptr = shared_ptr< CorrespondenceEstimationBase< PointSource, PointTarget, float > >

using	ConstPtr = shared_ptr< const CorrespondenceEstimationBase< PointSource, PointTarget, float > >

using	KdTree = pcl::search::KdTree< PointTarget >

using	KdTreePtr = typename KdTree::Ptr

using	KdTreeReciprocal = pcl::search::KdTree< PointSource >

using	KdTreeReciprocalPtr = typename KdTree::Ptr

using	PointCloudSource = pcl::PointCloud< PointSource >

using	PointCloudSourcePtr = typename PointCloudSource::Ptr

using	PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

using	PointCloudTarget = pcl::PointCloud< PointTarget >

using	PointCloudTargetPtr = typename PointCloudTarget::Ptr

using	PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

using	PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

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

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

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

virtual	~CorrespondenceEstimationBackProjection ()
	Empty destructor. More...

void	setSourceNormals (const NormalsConstPtr &normals)
	Set the normals computed on the source point cloud. More...

NormalsConstPtr	getSourceNormals () const
	Get the normals of the source point cloud. More...

void	setTargetNormals (const NormalsConstPtr &normals)
	Set the normals computed on the target point cloud. More...

NormalsConstPtr	getTargetNormals () const
	Get the normals of the target point cloud. More...

bool	requiresSourceNormals () const
	See if this rejector requires source normals. More...

void	setSourceNormals (pcl::PCLPointCloud2::ConstPtr cloud2)
	Blob method for setting the source normals. More...

bool	requiresTargetNormals () const
	See if this rejector requires target normals. More...

void	setTargetNormals (pcl::PCLPointCloud2::ConstPtr cloud2)
	Method for setting the target normals. More...

void	determineCorrespondences (pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())
	Determine the correspondences between input and target cloud. More...

virtual void	determineReciprocalCorrespondences (pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())
	Determine the reciprocal correspondences between input and target cloud. More...

void	setKSearch (unsigned int k)
	Set the number of nearest neighbours to be considered in the target point cloud. More...

unsigned int	getKSearch () const
	Get the number of nearest neighbours considered in the target point cloud for computing correspondences. More...

virtual CorrespondenceEstimationBase< PointSource, PointTarget, Scalar >::Ptr	clone () const
	Clone and cast to CorrespondenceEstimationBase. More...

Public Member Functions inherited from pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >
	CorrespondenceEstimationBase ()
	Empty constructor. More...

	~CorrespondenceEstimationBase ()
	Empty destructor. More...

void	setInputSource (const PointCloudSourceConstPtr &cloud)
	Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More...

const PointCloudSourceConstPtr	getInputSource ()
	Get a pointer to the input point cloud dataset target. More...

void	setInputTarget (const PointCloudTargetConstPtr &cloud)
	Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) More...

const PointCloudTargetConstPtr	getInputTarget ()
	Get a pointer to the input point cloud dataset target. More...

virtual bool	requiresSourceNormals () const
	See if this rejector requires source normals. More...

virtual bool	requiresTargetNormals () const
	See if this rejector requires target normals. More...

void	setIndicesSource (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represent the input source point cloud. More...

const IndicesPtr	getIndicesSource ()
	Get a pointer to the vector of indices used for the source dataset. More...

void	setIndicesTarget (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represent the input target point cloud. More...

const IndicesPtr	getIndicesTarget ()
	Get a pointer to the vector of indices used for the target dataset. More...

void	setSearchMethodTarget (const KdTreePtr &tree, bool force_no_recompute=false)
	Provide a pointer to the search object used to find correspondences in the target cloud. More...

KdTreePtr	getSearchMethodTarget () const
	Get a pointer to the search method used to find correspondences in the target cloud. More...

void	setSearchMethodSource (const KdTreeReciprocalPtr &tree, bool force_no_recompute=false)
	Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding). More...

KdTreeReciprocalPtr	getSearchMethodSource () const
	Get a pointer to the search method used to find correspondences in the source cloud. More...

void	setPointRepresentation (const PointRepresentationConstPtr &point_representation)
	Provide a boost shared pointer to the PointRepresentation to be used when searching for nearest neighbors. More...

virtual CorrespondenceEstimationBase< PointSource, PointTarget, float >::Ptr	clone () const=0
	Clone and cast to CorrespondenceEstimationBase. More...

Public Member Functions inherited from pcl::PCLBase< PointSource >
	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...

const PointCloudConstPtr	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...

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

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

Protected Member Functions
bool	initCompute ()
	Internal computation initialization. More...

Protected Member Functions inherited from pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >
const std::string &	getClassName () const
	Abstract class get name method. More...

bool	initCompute ()
	Internal computation initialization. More...

bool	initComputeReciprocal ()
	Internal computation initialization for reciprocal correspondences. More...

Protected Member Functions inherited from pcl::PCLBase< PointSource >
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::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >
std::string	corr_name_
	The correspondence estimation method name. More...

KdTreePtr	tree_
	A pointer to the spatial search object used for the target dataset. More...

KdTreeReciprocalPtr	tree_reciprocal_
	A pointer to the spatial search object used for the source dataset. More...

PointCloudTargetConstPtr	target_
	The input point cloud dataset target. More...

IndicesPtr	target_indices_
	The target point cloud dataset indices. More...

PointRepresentationConstPtr	point_representation_
	The point representation used (internal). More...

PointCloudTargetPtr	input_transformed_
	The transformed input source point cloud dataset. More...

std::vector< pcl::PCLPointField >	input_fields_
	The types of input point fields available. More...

bool	target_cloud_updated_
	Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. More...

bool	source_cloud_updated_
	Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. More...

bool	force_no_recompute_
	A flag which, if set, means the tree operating on the target cloud will never be recomputed. More...

bool	force_no_recompute_reciprocal_
	A flag which, if set, means the tree operating on the source cloud will never be recomputed. More...

Protected Attributes inherited from pcl::PCLBase< PointSource >
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 PointSource, typename PointTarget, typename NormalT, typename Scalar = float>
class pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >

CorrespondenceEstimationBackprojection computes correspondences as points in the target cloud which have minimum

Author: Suat Gedikli

Definition at line 56 of file correspondence_estimation_backprojection.h.

Member Typedef Documentation

ConstPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::ConstPtr = shared_ptr<const CorrespondenceEstimationBackProjection<PointSource, PointTarget, NormalT, Scalar> >

Definition at line 66 of file correspondence_estimation_backprojection.h.

KdTree

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::KdTree = pcl::search::KdTree<PointTarget>

Definition at line 81 of file correspondence_estimation_backprojection.h.

KdTreePtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::KdTreePtr = typename KdTree::Ptr

Definition at line 82 of file correspondence_estimation_backprojection.h.

NormalsConstPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::NormalsConstPtr = typename PointCloudNormals::ConstPtr

Definition at line 94 of file correspondence_estimation_backprojection.h.

NormalsPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::NormalsPtr = typename PointCloudNormals::Ptr

Definition at line 93 of file correspondence_estimation_backprojection.h.

PointCloudNormals

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudNormals = pcl::PointCloud<NormalT>

Definition at line 92 of file correspondence_estimation_backprojection.h.

PointCloudSource

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudSource = pcl::PointCloud<PointSource>

Definition at line 84 of file correspondence_estimation_backprojection.h.

PointCloudSourceConstPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr

Definition at line 86 of file correspondence_estimation_backprojection.h.

PointCloudSourcePtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudSourcePtr = typename PointCloudSource::Ptr

Definition at line 85 of file correspondence_estimation_backprojection.h.

PointCloudTarget

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudTarget = pcl::PointCloud<PointTarget>

Definition at line 88 of file correspondence_estimation_backprojection.h.

PointCloudTargetConstPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr

Definition at line 90 of file correspondence_estimation_backprojection.h.

PointCloudTargetPtr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::PointCloudTargetPtr = typename PointCloudTarget::Ptr

Definition at line 89 of file correspondence_estimation_backprojection.h.

Ptr

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

using pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::Ptr = shared_ptr<CorrespondenceEstimationBackProjection<PointSource, PointTarget, NormalT, Scalar> >

Definition at line 62 of file correspondence_estimation_backprojection.h.

Constructor & Destructor Documentation

CorrespondenceEstimationBackProjection()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::CorrespondenceEstimationBackProjection ( )

inline

Empty constructor.

Note: Sets the number of neighbors to be considered in the target point cloud (k_) to 10.

Definition at line 101 of file correspondence_estimation_backprojection.h.

References pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >::corr_name_.

~CorrespondenceEstimationBackProjection()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

virtual pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::~CorrespondenceEstimationBackProjection ( )

inlinevirtual

Empty destructor.

Definition at line 108 of file correspondence_estimation_backprojection.h.

Member Function Documentation

clone()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

virtual CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::Ptr pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::clone ( ) const

inlinevirtual

Clone and cast to CorrespondenceEstimationBase.

Definition at line 222 of file correspondence_estimation_backprojection.h.

determineCorrespondences()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::determineCorrespondences	(	pcl::Correspondences &	correspondences,
		double	max_distance = `std::numeric_limits<double>::max()`
	)

virtual

Determine the correspondences between input and target cloud.

Parameters

[out]	correspondences	the found correspondences (index of query point, index of target point, distance)
[in]	max_distance	maximum distance between the normal on the source point cloud and the corresponding point in the target point cloud

Implements pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >.

Definition at line 69 of file correspondence_estimation_backprojection.hpp.

References pcl::copyPoint(), pcl::Correspondence::distance, pcl::Correspondence::index_match, and pcl::Correspondence::index_query.

determineReciprocalCorrespondences()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::determineReciprocalCorrespondences	(	pcl::Correspondences &	correspondences,
		double	max_distance = `std::numeric_limits<double>::max()`
	)

virtual

Determine the reciprocal correspondences between input and target cloud.

A correspondence is considered reciprocal if both Src_i has Tgt_i as a correspondence, and Tgt_i has Src_i as one.

Parameters

[out]	correspondences	the found correspondences (index of query and target point, distance)
[in]	max_distance	maximum allowed distance between correspondences

Implements pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >.

Definition at line 168 of file correspondence_estimation_backprojection.hpp.

References pcl::copyPoint(), pcl::Correspondence::distance, pcl::Correspondence::index_match, and pcl::Correspondence::index_query.

getKSearch()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

unsigned int pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::getKSearch ( ) const

inline

Get the number of nearest neighbours considered in the target point cloud for computing correspondences.

By default we use k = 10 nearest neighbors.

Definition at line 215 of file correspondence_estimation_backprojection.h.

getSourceNormals()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

NormalsConstPtr pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::getSourceNormals ( ) const

inline

Get the normals of the source point cloud.

Definition at line 122 of file correspondence_estimation_backprojection.h.

getTargetNormals()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

NormalsConstPtr pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::getTargetNormals ( ) const

inline

Get the normals of the target point cloud.

Definition at line 139 of file correspondence_estimation_backprojection.h.

initCompute()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar >

bool pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::initCompute

protected

Internal computation initialization.

Definition at line 52 of file correspondence_estimation_backprojection.hpp.

requiresSourceNormals()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

bool pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::requiresSourceNormals ( ) const

inline

See if this rejector requires source normals.

Definition at line 146 of file correspondence_estimation_backprojection.h.

requiresTargetNormals()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

bool pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::requiresTargetNormals ( ) const

inline

See if this rejector requires target normals.

Definition at line 162 of file correspondence_estimation_backprojection.h.

setKSearch()

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setKSearch ( unsigned int k )

inline

Set the number of nearest neighbours to be considered in the target point cloud.

By default, we use k = 10 nearest neighbors.

Parameters

[in] k the number of nearest neighbours to be considered

Definition at line 205 of file correspondence_estimation_backprojection.h.

setSourceNormals() [1/2]

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals ( const NormalsConstPtr & normals )

inline

Set the normals computed on the source point cloud.

Parameters

[in] normals the normals computed for the source cloud

Definition at line 114 of file correspondence_estimation_backprojection.h.

Referenced by pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals().

setSourceNormals() [2/2]

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals ( pcl::PCLPointCloud2::ConstPtr cloud2 )

inlinevirtual

Blob method for setting the source normals.

Reimplemented from pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >.

Definition at line 153 of file correspondence_estimation_backprojection.h.

References pcl::fromPCLPointCloud2(), and pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals().

setTargetNormals() [1/2]

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals ( const NormalsConstPtr & normals )

inline

Set the normals computed on the target point cloud.

Parameters

[in] normals the normals computed for the target cloud

Definition at line 131 of file correspondence_estimation_backprojection.h.

Referenced by pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals().

setTargetNormals() [2/2]

template<typename PointSource , typename PointTarget , typename NormalT , typename Scalar = float>

void pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals ( pcl::PCLPointCloud2::ConstPtr cloud2 )

inlinevirtual

Method for setting the target normals.

Reimplemented from pcl::registration::CorrespondenceEstimationBase< PointSource, PointTarget, float >.

Definition at line 169 of file correspondence_estimation_backprojection.h.

References pcl::fromPCLPointCloud2(), and pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals().

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

pcl/registration/correspondence_estimation_backprojection.h
pcl/registration/impl/correspondence_estimation_backprojection.hpp

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1registration_1_1_correspondence_estimation_back_projection.html

Name	PointCloudLibrary
Version
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Last Updated	2021-12-29T19:25:09Z

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

template<typename PointSource, typename PointTarget, typename NormalT, typename Scalar = float> class pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >

Member Typedef Documentation

ConstPtr

KdTree

KdTreePtr

NormalsConstPtr

NormalsPtr

PointCloudNormals

PointCloudSource

PointCloudSourceConstPtr

PointCloudSourcePtr

PointCloudTarget

PointCloudTargetConstPtr

PointCloudTargetPtr

Ptr

Constructor & Destructor Documentation

CorrespondenceEstimationBackProjection()

~CorrespondenceEstimationBackProjection()

Member Function Documentation

clone()

determineCorrespondences()

determineReciprocalCorrespondences()

getKSearch()

getSourceNormals()

getTargetNormals()

initCompute()

requiresSourceNormals()

requiresTargetNormals()

setKSearch()

setSourceNormals() [1/2]

setSourceNormals() [2/2]

setTargetNormals() [1/2]

setTargetNormals() [2/2]

template<typename PointSource, typename PointTarget, typename NormalT, typename Scalar = float>
class pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >