Calculates the weighted average and the covariance matrix. More...

#include <pcl/common/vector_average.h>

Public Types
using	VectorType = Eigen::Matrix< real, dimension, 1 >

using	MatrixType = Eigen::Matrix< real, dimension, dimension >

Public Member Functions
	VectorAverage ()
	Constructor - dimension gives the size of the vectors to work with. More...

void	reset ()
	Reset the object to work with a new data set. More...

const VectorType &	getMean () const
	Get the mean of the added vectors. More...

const MatrixType &	getCovariance () const
	Get the covariance matrix of the added vectors. More...

real	getAccumulatedWeight () const
	Get the summed up weight of all added vectors. More...

unsigned int	getNoOfSamples ()
	Get the number of added vectors. More...

void	add (const VectorType &sample, real weight=1.0)
	Add a new sample. More...

void	doPCA (VectorType &eigen_values, VectorType &eigen_vector1, VectorType &eigen_vector2, VectorType &eigen_vector3) const
	Do Principal component analysis. More...

void	doPCA (VectorType &eigen_values) const
	Do Principal component analysis. More...

void	getEigenVector1 (VectorType &eigen_vector1) const
	Get the eigenvector corresponding to the smallest eigenvalue. More...

void	doPCA (Eigen::Matrix< float, 3, 1 > &eigen_values, Eigen::Matrix< float, 3, 1 > &eigen_vector1, Eigen::Matrix< float, 3, 1 > &eigen_vector2, Eigen::Matrix< float, 3, 1 > &eigen_vector3) const

void	doPCA (Eigen::Matrix< float, 3, 1 > &eigen_values) const

void	getEigenVector1 (Eigen::Matrix< float, 3, 1 > &eigen_vector1) const

void	doPCA (Eigen::Matrix< double, 3, 1 > &eigen_values, Eigen::Matrix< double, 3, 1 > &eigen_vector1, Eigen::Matrix< double, 3, 1 > &eigen_vector2, Eigen::Matrix< double, 3, 1 > &eigen_vector3) const

void	doPCA (Eigen::Matrix< double, 3, 1 > &eigen_values) const

void	getEigenVector1 (Eigen::Matrix< double, 3, 1 > &eigen_vector1) const

Protected Attributes
unsigned int	noOfSamples_ = 0

real	accumulatedWeight_ = 0

VectorType	mean_ = VectorType::Identity ()

MatrixType	covariance_ = MatrixType::Identity ()

Detailed Description

template<typename real, int dimension>
class pcl::VectorAverage< real, dimension >

Calculates the weighted average and the covariance matrix.

A class to calculate the weighted average and the covariance matrix of a set of vectors with given weights. The original data is not saved. Mean and covariance are calculated iteratively.

Author: Bastian Steder

Definition at line 55 of file vector_average.h.

Member Typedef Documentation

◆ MatrixType

template<typename real , int dimension>

using pcl::VectorAverage< real, dimension >::MatrixType = Eigen::Matrix<real, dimension, dimension>

Definition at line 59 of file vector_average.h.

◆ VectorType

template<typename real , int dimension>

using pcl::VectorAverage< real, dimension >::VectorType = Eigen::Matrix<real, dimension, 1>

Definition at line 58 of file vector_average.h.

Constructor & Destructor Documentation

◆ VectorAverage()

template<typename real , int dimension>

pcl::VectorAverage< real, dimension >::VectorAverage

Constructor - dimension gives the size of the vectors to work with.

Definition at line 48 of file vector_average.hpp.

Member Function Documentation

◆ add()

template<typename real , int dimension>

void pcl::VectorAverage< real, dimension >::add	(	const VectorType &	sample,
		real	weight = `1.0`
	)

inline

Add a new sample.

Definition at line 63 of file vector_average.hpp.

Referenced by pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::RangeImage::getCurvature(), pcl::RangeImage::getNormal(), pcl::RangeImage::getSurfaceInformation(), pcl::GridProjection< PointNT >::getVectorAtPoint(), and pcl::GridProjection< PointNT >::getVectorAtPointKNN().

◆ doPCA() [1/6]

void pcl::VectorAverage< double, 3 >::doPCA ( Eigen::Matrix< double, 3, 1 > & eigen_values ) const

inline

Definition at line 188 of file vector_average.hpp.

References pcl::computeRoots().

◆ doPCA() [2/6]

void pcl::VectorAverage< double, 3 >::doPCA	(	Eigen::Matrix< double, 3, 1 > &	eigen_values,
		Eigen::Matrix< double, 3, 1 > &	eigen_vector1,
		Eigen::Matrix< double, 3, 1 > &	eigen_vector2,
		Eigen::Matrix< double, 3, 1 > &	eigen_vector3
	)		const

inline

Definition at line 177 of file vector_average.hpp.

References pcl::eigen33().

◆ doPCA() [3/6]

void pcl::VectorAverage< float, 3 >::doPCA ( Eigen::Matrix< float, 3, 1 > & eigen_values ) const

inline

Definition at line 158 of file vector_average.hpp.

References pcl::computeRoots().

◆ doPCA() [4/6]

void pcl::VectorAverage< float, 3 >::doPCA	(	Eigen::Matrix< float, 3, 1 > &	eigen_values,
		Eigen::Matrix< float, 3, 1 > &	eigen_vector1,
		Eigen::Matrix< float, 3, 1 > &	eigen_vector2,
		Eigen::Matrix< float, 3, 1 > &	eigen_vector3
	)		const

inline

Definition at line 147 of file vector_average.hpp.

References pcl::eigen33().

◆ doPCA() [5/6]

template<typename real , int dimension>

void pcl::VectorAverage< real, dimension >::doPCA ( VectorType & eigen_values ) const

inline

Do Principal component analysis.

Definition at line 108 of file vector_average.hpp.

◆ doPCA() [6/6]

template<typename real , int dimension>

void pcl::VectorAverage< real, dimension >::doPCA	(	VectorType &	eigen_values,
		VectorType &	eigen_vector1,
		VectorType &	eigen_vector2,
		VectorType &	eigen_vector3
	)		const

inline

Do Principal component analysis.

Definition at line 84 of file vector_average.hpp.

Referenced by pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::RangeImage::getCurvature(), pcl::RangeImage::getNormal(), and pcl::RangeImage::getSurfaceInformation().

◆ getAccumulatedWeight()

template<typename real , int dimension>

real pcl::VectorAverage< real, dimension >::getAccumulatedWeight ( ) const

inline

Get the summed up weight of all added vectors.

Definition at line 79 of file vector_average.h.

References pcl::VectorAverage< real, dimension >::accumulatedWeight_.

◆ getCovariance()

template<typename real , int dimension>

const MatrixType& pcl::VectorAverage< real, dimension >::getCovariance ( ) const

inline

Get the covariance matrix of the added vectors.

Definition at line 75 of file vector_average.h.

References pcl::VectorAverage< real, dimension >::covariance_.

◆ getEigenVector1() [1/3]

void pcl::VectorAverage< double, 3 >::getEigenVector1 ( Eigen::Matrix< double, 3, 1 > & eigen_vector1 ) const

inline

Definition at line 194 of file vector_average.hpp.

References pcl::eigen33().

◆ getEigenVector1() [2/3]

void pcl::VectorAverage< float, 3 >::getEigenVector1 ( Eigen::Matrix< float, 3, 1 > & eigen_vector1 ) const

inline

Definition at line 164 of file vector_average.hpp.

References pcl::eigen33().

◆ getEigenVector1() [3/3]

template<typename real , int dimension>

void pcl::VectorAverage< real, dimension >::getEigenVector1 ( VectorType & eigen_vector1 ) const

inline

Get the eigenvector corresponding to the smallest eigenvalue.

Definition at line 121 of file vector_average.hpp.

Referenced by pcl::GridProjection< PointNT >::getVectorAtPointKNN().

◆ getMean()

template<typename real , int dimension>

const VectorType& pcl::VectorAverage< real, dimension >::getMean ( ) const

inline

Get the mean of the added vectors.

Definition at line 71 of file vector_average.h.

References pcl::VectorAverage< real, dimension >::mean_.

Referenced by pcl::RangeImage::getNormal(), pcl::RangeImage::getSurfaceInformation(), and pcl::GridProjection< PointNT >::getVectorAtPoint().

◆ getNoOfSamples()

template<typename real , int dimension>

unsigned int pcl::VectorAverage< real, dimension >::getNoOfSamples ( )

inline

Get the number of added vectors.

Definition at line 83 of file vector_average.h.

References pcl::VectorAverage< real, dimension >::noOfSamples_.

Referenced by pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::RangeImage::getCurvature(), pcl::RangeImage::getNormal(), and pcl::RangeImage::getSurfaceInformation().

◆ reset()

template<typename real , int dimension>

void pcl::VectorAverage< real, dimension >::reset

inline

Reset the object to work with a new data set.

Definition at line 54 of file vector_average.hpp.

Member Data Documentation

◆ accumulatedWeight_

template<typename real , int dimension>

real pcl::VectorAverage< real, dimension >::accumulatedWeight_ = 0

protected

Definition at line 111 of file vector_average.h.

Referenced by pcl::VectorAverage< real, dimension >::getAccumulatedWeight().

◆ covariance_

template<typename real , int dimension>

MatrixType pcl::VectorAverage< real, dimension >::covariance_ = MatrixType::Identity ()

protected

Definition at line 113 of file vector_average.h.

Referenced by pcl::VectorAverage< real, dimension >::getCovariance().

◆ mean_

template<typename real , int dimension>

VectorType pcl::VectorAverage< real, dimension >::mean_ = VectorType::Identity ()

protected

Definition at line 112 of file vector_average.h.

Referenced by pcl::VectorAverage< real, dimension >::getMean().

◆ noOfSamples_

template<typename real , int dimension>

unsigned int pcl::VectorAverage< real, dimension >::noOfSamples_ = 0

protected

Definition at line 110 of file vector_average.h.

Referenced by pcl::VectorAverage< real, dimension >::getNoOfSamples().

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

pcl/common/vector_average.h
pcl/common/impl/vector_average.hpp

Public Types

Public Member Functions

Protected Attributes

Detailed Description

template<typename real, int dimension> class pcl::VectorAverage< real, dimension >

Member Typedef Documentation

◆ MatrixType

◆ VectorType

Constructor & Destructor Documentation

◆ VectorAverage()

Member Function Documentation

◆ add()

◆ doPCA() [1/6]

◆ doPCA() [2/6]

◆ doPCA() [3/6]

◆ doPCA() [4/6]

◆ doPCA() [5/6]

◆ doPCA() [6/6]

◆ getAccumulatedWeight()

◆ getCovariance()

◆ getEigenVector1() [1/3]

◆ getEigenVector1() [2/3]

◆ getEigenVector1() [3/3]

◆ getMean()

◆ getNoOfSamples()

◆ reset()

Member Data Documentation

◆ accumulatedWeight_

◆ covariance_

◆ mean_

◆ noOfSamples_

template<typename real, int dimension>
class pcl::VectorAverage< real, dimension >