Point Cloud Library (PCL)  1.14.0-dev
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pcl::CovarianceSampling< PointT, PointNT > Class Template Reference

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 PointToperator[] (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:

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]outputthe 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]indicesthe 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_matrixuser 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_matrixthe 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]normalsthe 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]samplesthe 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

◆ 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: