Point Cloud sampling based on the 6D covariances. More...

#include <pcl/filters/covariance_sampling.h>

Inheritance diagram for pcl::CovarianceSampling< PointT, PointNT >:

Collaboration diagram for pcl::CovarianceSampling< PointT, PointNT >:

Public Types
using	Ptr = shared_ptr< CovarianceSampling< PointT, PointNT > >

using	ConstPtr = shared_ptr< const CovarianceSampling< PointT, PointNT > >

Public Types inherited from pcl::FilterIndices< PointT >
using	PointCloud = pcl::PointCloud< PointT >

using	Ptr = shared_ptr< FilterIndices< PointT > >

using	ConstPtr = shared_ptr< const FilterIndices< PointT > >

Public Types inherited from pcl::Filter< PointT >
using	Ptr = shared_ptr< Filter< PointT > >

using	ConstPtr = shared_ptr< const Filter< PointT > >

using	PointCloud = pcl::PointCloud< PointT >

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

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

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

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

void	setNumberOfSamples (unsigned int samples)
	Set number of indices to be sampled. More...

unsigned int	getNumberOfSamples () const
	Get the value of the internal num_samples_ parameter. More...

void	setNormals (const NormalsConstPtr &normals)
	Set the normals computed on the input point cloud. More...

NormalsConstPtr	getNormals () const
	Get the normals computed on the input point cloud. More...

double	computeConditionNumber ()
	Compute the condition number of the input point cloud. More...

bool	computeCovarianceMatrix (Eigen::Matrix< double, 6, 6 > &covariance_matrix)
	Computes the covariance matrix of the input cloud. More...

Public Member Functions inherited from pcl::FilterIndices< PointT >
	FilterIndices (bool extract_removed_indices=false)
	Constructor. More...

void	filter (Indices &indices)
	Calls the filtering method and returns the filtered point cloud indices. More...

void	setNegative (bool negative)
	Set whether the regular conditions for points filtering should apply, or the inverted conditions. More...

bool	getNegative () const
	Get whether the regular conditions for points filtering should apply, or the inverted conditions. More...

void	setKeepOrganized (bool keep_organized)
	Set whether the filtered points should be kept and set to the value given through setUserFilterValue (default: NaN), or removed from the PointCloud, thus potentially breaking its organized structure. More...

bool	getKeepOrganized () const
	Get whether the filtered points should be kept and set to the value given through setUserFilterValue (default = NaN), or removed from the PointCloud, thus potentially breaking its organized structure. More...

void	setUserFilterValue (float value)
	Provide a value that the filtered points should be set to instead of removing them. More...

Public Member Functions inherited from pcl::Filter< PointT >
	Filter (bool extract_removed_indices=false)
	Empty constructor. More...

IndicesConstPtr const	getRemovedIndices () const
	Get the point indices being removed. More...

void	getRemovedIndices (PointIndices &pi)
	Get the point indices being removed. More...

void	filter (PointCloud &output)
	Calls the filtering method and returns the filtered dataset in output. More...

Public Member Functions inherited from pcl::PCLBase< PointT >
	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 PointT &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code. More...

Static Public Member Functions
static double	computeConditionNumber (const Eigen::Matrix< double, 6, 6 > &covariance_matrix)
	Compute the condition number of the input point cloud. More...

Protected Member Functions
bool	initCompute ()

void	applyFilter (Cloud &output) override
	Sample of point indices into a separate PointCloud. More...

void	applyFilter (Indices &indices) override
	Sample of point indices. More...

Protected Member Functions inherited from pcl::FilterIndices< PointT >
void	applyFilter (PointCloud &output) override
	Abstract filter method for point cloud. More...

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

Protected Member Functions inherited from pcl::PCLBase< PointT >
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...

Static Protected Member Functions
static bool	sort_dot_list_function (std::pair< int, double > a, std::pair< int, double > b)

Protected Attributes
unsigned int	num_samples_
	Number of indices that will be returned. More...

NormalsConstPtr	input_normals_
	The normals computed at each point in the input cloud. More...

std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > >	scaled_points_

Protected Attributes inherited from pcl::FilterIndices< PointT >
bool	negative_ {false}
	False = normal filter behavior (default), true = inverted behavior. More...

bool	keep_organized_ {false}
	False = remove points (default), true = redefine points, keep structure. More...

float	user_filter_value_
	The user given value that the filtered point dimensions should be set to (default = NaN). More...

Protected Attributes inherited from pcl::Filter< PointT >
IndicesPtr	removed_indices_
	Indices of the points that are removed. More...

std::string	filter_name_
	The filter name. More...

bool	extract_removed_indices_
	Set to true if we want to return the indices of the removed points. More...

Protected Attributes inherited from pcl::PCLBase< PointT >
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 PointT, typename PointNT>
class pcl::CovarianceSampling< PointT, PointNT >

Point Cloud sampling based on the 6D covariances.

It selects the points such that the resulting cloud is as stable as possible for being registered (against a copy of itself) with ICP. The algorithm adds points to the resulting cloud incrementally, while trying to keep all the 6 eigenvalues of the covariance matrix as close to each other as possible. This class also comes with the computeConditionNumber method that returns a number which shows how stable a point cloud will be when used as input for ICP (the closer the value it is to 1.0, the better).

Based on the following publication:

"Geometrically Stable Sampling for the ICP Algorithm" - N. Gelfand, L. Ikemoto, S. Rusinkiewicz, M. Levoy

Author: Alexandru E. Ichim, alex..nosp@m.e.ic.nosp@m.him@g.nosp@m.mail.nosp@m..com

Definition at line 62 of file covariance_sampling.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointT , typename PointNT >

using pcl::CovarianceSampling< PointT, PointNT >::ConstPtr = shared_ptr< const CovarianceSampling<PointT, PointNT> >

Definition at line 77 of file covariance_sampling.h.

◆ Ptr

template<typename PointT , typename PointNT >

using pcl::CovarianceSampling< PointT, PointNT >::Ptr = shared_ptr< CovarianceSampling<PointT, PointNT> >

Definition at line 76 of file covariance_sampling.h.

Constructor & Destructor Documentation

◆ CovarianceSampling()

template<typename PointT , typename PointNT >

pcl::CovarianceSampling< PointT, PointNT >::CovarianceSampling ( )

inline

Empty constructor.

Definition at line 80 of file covariance_sampling.h.

References pcl::Filter< PointT >::filter_name_.

Member Function Documentation

◆ applyFilter() [1/2]

template<typename PointT , typename PointNT >

void pcl::CovarianceSampling< PointT, PointNT >::applyFilter ( Cloud & output )

overrideprotectedvirtual

Sample of point indices into a separate PointCloud.

Parameters

[out] output the resultant point cloud

Implements pcl::Filter< PointT >.

Definition at line 213 of file covariance_sampling.hpp.

◆ applyFilter() [2/2]

template<typename PointT , typename PointNT >

void pcl::CovarianceSampling< PointT, PointNT >::applyFilter ( Indices & indices )

overrideprotectedvirtual

Sample of point indices.

Parameters

[out] indices the resultant point cloud indices

TODO figure out how to fill the candidate_indices - see subsequent paper paragraphs

Implements pcl::FilterIndices< PointT >.

Definition at line 131 of file covariance_sampling.hpp.

References pcl::computeCovarianceMatrix().

◆ computeConditionNumber() [1/2]

template<typename PointT , typename PointNT >

double pcl::CovarianceSampling< PointT, PointNT >::computeConditionNumber

Compute the condition number of the input point cloud.

The condition number is the ratio between the largest and smallest eigenvalues of the 6x6 covariance matrix of the cloud. The closer this number is to 1.0, the more stable the cloud is for ICP registration.

Returns: the condition number

Definition at line 86 of file covariance_sampling.hpp.

References pcl::computeCovarianceMatrix().

◆ computeConditionNumber() [2/2]

template<typename PointT , typename PointNT >

double pcl::CovarianceSampling< PointT, PointNT >::computeConditionNumber ( const Eigen::Matrix< double, 6, 6 > & covariance_matrix )

static

Compute the condition number of the input point cloud.

The condition number is the ratio between the largest and smallest eigenvalues of the 6x6 covariance matrix of the cloud. The closer this number is to 1.0, the more stable the cloud is for ICP registration.

Parameters

[in] covariance_matrix user given covariance matrix. Assumed to be self adjoint/symmetric.

Returns: the condition number

Definition at line 98 of file covariance_sampling.hpp.

◆ computeCovarianceMatrix()

template<typename PointT , typename PointNT >

bool pcl::CovarianceSampling< PointT, PointNT >::computeCovarianceMatrix ( Eigen::Matrix< double, 6, 6 > & covariance_matrix )

Computes the covariance matrix of the input cloud.

Parameters

[out] covariance_matrix the computed covariance matrix.

Returns: whether the computation succeeded or not

Definition at line 109 of file covariance_sampling.hpp.

◆ getNormals()

template<typename PointT , typename PointNT >

NormalsConstPtr pcl::CovarianceSampling< PointT, PointNT >::getNormals ( ) const

inline

Get the normals computed on the input point cloud.

Definition at line 104 of file covariance_sampling.h.

References pcl::CovarianceSampling< PointT, PointNT >::input_normals_.

◆ getNumberOfSamples()

template<typename PointT , typename PointNT >

unsigned int pcl::CovarianceSampling< PointT, PointNT >::getNumberOfSamples ( ) const

inline

Get the value of the internal num_samples_ parameter.

Definition at line 92 of file covariance_sampling.h.

References pcl::CovarianceSampling< PointT, PointNT >::num_samples_.

◆ initCompute()

template<typename PointT , typename PointNT >

bool pcl::CovarianceSampling< PointT, PointNT >::initCompute

protected

Definition at line 50 of file covariance_sampling.hpp.

◆ setNormals()

template<typename PointT , typename PointNT >

void pcl::CovarianceSampling< PointT, PointNT >::setNormals ( const NormalsConstPtr & normals )

inline

Set the normals computed on the input point cloud.

Parameters

[in] normals the normals computed for the input cloud

Definition at line 99 of file covariance_sampling.h.

References pcl::CovarianceSampling< PointT, PointNT >::input_normals_.

◆ setNumberOfSamples()

template<typename PointT , typename PointNT >

void pcl::CovarianceSampling< PointT, PointNT >::setNumberOfSamples ( unsigned int samples )

inline

Set number of indices to be sampled.

Parameters

[in] samples the number of sample indices

Definition at line 87 of file covariance_sampling.h.

References pcl::CovarianceSampling< PointT, PointNT >::num_samples_.

◆ sort_dot_list_function()

template<typename PointT , typename PointNT >

static bool pcl::CovarianceSampling< PointT, PointNT >::sort_dot_list_function	(	std::pair< int, double >	a,
		std::pair< int, double >	b
	)

inlinestaticprotected

Definition at line 158 of file covariance_sampling.h.

Member Data Documentation

◆ input_normals_

template<typename PointT , typename PointNT >

NormalsConstPtr pcl::CovarianceSampling< PointT, PointNT >::input_normals_

protected

The normals computed at each point in the input cloud.

Definition at line 138 of file covariance_sampling.h.

Referenced by pcl::CovarianceSampling< PointT, PointNT >::getNormals(), and pcl::CovarianceSampling< PointT, PointNT >::setNormals().

◆ num_samples_

template<typename PointT , typename PointNT >

unsigned int pcl::CovarianceSampling< PointT, PointNT >::num_samples_

protected

Number of indices that will be returned.

Definition at line 135 of file covariance_sampling.h.

Referenced by pcl::CovarianceSampling< PointT, PointNT >::getNumberOfSamples(), and pcl::CovarianceSampling< PointT, PointNT >::setNumberOfSamples().

◆ scaled_points_

template<typename PointT , typename PointNT >

std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > pcl::CovarianceSampling< PointT, PointNT >::scaled_points_

protected

Definition at line 140 of file covariance_sampling.h.

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

pcl/filters/covariance_sampling.h
pcl/filters/impl/covariance_sampling.hpp

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Detailed Description

template<typename PointT, typename PointNT> class pcl::CovarianceSampling< PointT, PointNT >

Member Typedef Documentation

◆ ConstPtr

◆ Ptr

Constructor & Destructor Documentation

◆ CovarianceSampling()

Member Function Documentation

◆ applyFilter() [1/2]

◆ applyFilter() [2/2]

◆ computeConditionNumber() [1/2]

◆ computeConditionNumber() [2/2]

◆ computeCovarianceMatrix()

◆ getNormals()

◆ getNumberOfSamples()

◆ initCompute()

◆ setNormals()

◆ setNumberOfSamples()

◆ sort_dot_list_function()

Member Data Documentation

◆ input_normals_

◆ num_samples_

◆ scaled_points_

template<typename PointT, typename PointNT>
class pcl::CovarianceSampling< PointT, PointNT >