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Point Cloud Library (PCL)
1.6.0
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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. More... | |
| ~VectorAverage () | |
| Destructor. More... | |
| void | reset () |
| Reset the object to work with a new data set. More... | |
| const Eigen::Matrix< real, dimension, 1 > & | getMean () const |
| Get the mean of the added vectors. More... | |
| const Eigen::Matrix< real, dimension, dimension > & | 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 Eigen::Matrix< real, dimension, 1 > &sample, real weight=1.0) |
| Add a new sample. More... | |
| 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. More... | |
| void | doPCA (Eigen::Matrix< real, dimension, 1 > &eigen_values) const |
| Do Principal component analysis. More... | |
| void | getEigenVector1 (Eigen::Matrix< real, dimension, 1 > &eigen_vector1) const |
| Get the eigenvector corresponding to the smallest eigenvalue. More... | |
| 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.
Definition at line 52 of file vector_average.h.
| pcl::VectorAverage< real, dimension >::VectorAverage | ( | ) |
Constructor - dimension gives the size of the vectors to work with.
Definition at line 40 of file vector_average.hpp.
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Destructor.
Definition at line 59 of file vector_average.h.
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Add a new sample.
Definition at line 58 of file vector_average.hpp.
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Do Principal component analysis.
Definition at line 79 of file vector_average.hpp.
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Do Principal component analysis.
Definition at line 103 of file vector_average.hpp.
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Definition at line 142 of file vector_average.hpp.
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Definition at line 153 of file vector_average.hpp.
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Definition at line 172 of file vector_average.hpp.
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Definition at line 183 of file vector_average.hpp.
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Get the summed up weight of all added vectors.
Definition at line 76 of file vector_average.h.
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Get the covariance matrix of the added vectors.
Definition at line 72 of file vector_average.h.
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Get the eigenvector corresponding to the smallest eigenvalue.
Definition at line 116 of file vector_average.hpp.
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Definition at line 159 of file vector_average.hpp.
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Definition at line 189 of file vector_average.hpp.
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Get the mean of the added vectors.
Definition at line 68 of file vector_average.h.
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Get the number of added vectors.
Definition at line 80 of file vector_average.h.
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Reset the object to work with a new data set.
Definition at line 49 of file vector_average.hpp.
1.8.4