Point Cloud Library (PCL)
1.3.1
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Calculates the weighted average and the covariance matrix. More...
#include <pcl/common/vector_average.h>
Public Member Functions | |
VectorAverage () | |
Constructor - dimension gives the size of the vectors to work with. | |
~VectorAverage () | |
Destructor. | |
void | reset () |
Reset the object to work with a new data set. | |
const Eigen::Matrix< real, dimension, 1 > & | getMean () const |
Get the mean of the added vectors. | |
const Eigen::Matrix< real, dimension, dimension > & | getCovariance () const |
Get the covariance matrix of the added vectors. | |
real | getAccumulatedWeight () const |
Get the summed up weight of all added vectors. | |
unsigned int | getNoOfSamples () |
Get the number of added vectors. | |
void | add (const Eigen::Matrix< real, dimension, 1 > &sample, real weight=1.0) |
Add a new sample. | |
void | doPCA (Eigen::Matrix< real, dimension, 1 > &eigen_values, Eigen::Matrix< real, dimension, 1 > &eigen_vector1, Eigen::Matrix< real, dimension, 1 > &eigen_vector2, Eigen::Matrix< real, dimension, 1 > &eigen_vector3) const |
Do Principal component analysis. | |
void | doPCA (Eigen::Matrix< real, dimension, 1 > &eigen_values) const |
Do Principal component analysis. | |
void | getEigenVector1 (Eigen::Matrix< real, dimension, 1 > &eigen_vector1) const |
Get the eigenvector corresponding to the smallest eigenvalue. | |
template<> | |
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 |
template<> | |
void | doPCA (Eigen::Matrix< float, 3, 1 > &eigen_values) const |
template<> | |
void | getEigenVector1 (Eigen::Matrix< float, 3, 1 > &eigen_vector1) const |
template<> | |
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 |
template<> | |
void | doPCA (Eigen::Matrix< double, 3, 1 > &eigen_values) const |
template<> | |
void | getEigenVector1 (Eigen::Matrix< double, 3, 1 > &eigen_vector1) const |
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.
pcl::VectorAverage::VectorAverage | ( | ) |
Constructor - dimension gives the size of the vectors to work with.
Definition at line 38 of file vector_average.hpp.
pcl::VectorAverage::~VectorAverage | ( | ) | [inline] |
Destructor.
Definition at line 59 of file vector_average.h.
void pcl::VectorAverage::add | ( | const Eigen::Matrix< real, dimension, 1 > & | sample, |
real | weight = 1.0 |
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) | [inline] |
Add a new sample.
Definition at line 53 of file vector_average.hpp.
void pcl::VectorAverage::doPCA | ( | Eigen::Matrix< real, dimension, 1 > & | eigen_values, |
Eigen::Matrix< real, dimension, 1 > & | eigen_vector1, | ||
Eigen::Matrix< real, dimension, 1 > & | eigen_vector2, | ||
Eigen::Matrix< real, dimension, 1 > & | eigen_vector3 | ||
) | const [inline] |
Do Principal component analysis.
Definition at line 74 of file vector_average.hpp.
void pcl::VectorAverage::doPCA | ( | Eigen::Matrix< real, dimension, 1 > & | eigen_values | ) | const [inline] |
Do Principal component analysis.
Definition at line 98 of file vector_average.hpp.
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 137 of file vector_average.hpp.
void pcl::VectorAverage< float, 3 >::doPCA | ( | Eigen::Matrix< float, 3, 1 > & | eigen_values | ) | const [inline] |
Definition at line 148 of file vector_average.hpp.
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 167 of file vector_average.hpp.
void pcl::VectorAverage< double, 3 >::doPCA | ( | Eigen::Matrix< double, 3, 1 > & | eigen_values | ) | const [inline] |
Definition at line 178 of file vector_average.hpp.
real pcl::VectorAverage::getAccumulatedWeight | ( | ) | const [inline] |
Get the summed up weight of all added vectors.
Definition at line 76 of file vector_average.h.
const Eigen::Matrix<real, dimension, dimension>& pcl::VectorAverage::getCovariance | ( | ) | const [inline] |
Get the covariance matrix of the added vectors.
Definition at line 72 of file vector_average.h.
void pcl::VectorAverage::getEigenVector1 | ( | Eigen::Matrix< real, dimension, 1 > & | eigen_vector1 | ) | const [inline] |
Get the eigenvector corresponding to the smallest eigenvalue.
Definition at line 111 of file vector_average.hpp.
void pcl::VectorAverage< float, 3 >::getEigenVector1 | ( | Eigen::Matrix< float, 3, 1 > & | eigen_vector1 | ) | const [inline] |
Definition at line 154 of file vector_average.hpp.
void pcl::VectorAverage< double, 3 >::getEigenVector1 | ( | Eigen::Matrix< double, 3, 1 > & | eigen_vector1 | ) | const [inline] |
Definition at line 184 of file vector_average.hpp.
const Eigen::Matrix<real, dimension, 1>& pcl::VectorAverage::getMean | ( | ) | const [inline] |
Get the mean of the added vectors.
Definition at line 68 of file vector_average.h.
unsigned int pcl::VectorAverage::getNoOfSamples | ( | ) | [inline] |
Get the number of added vectors.
Definition at line 80 of file vector_average.h.
void pcl::VectorAverage::reset | ( | ) | [inline] |
Reset the object to work with a new data set.
Definition at line 44 of file vector_average.hpp.