vector_average.h
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#ifndef PCL_COMMON_VECTOR_AVERAGE_H
#define PCL_COMMON_VECTOR_AVERAGE_H
#include <pcl/common/eigen.h>
namespace pcl
{
/** \brief 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
* \ingroup common
*/
template <typename real, int dimension>
class VectorAverage
{
public:
//-----CONSTRUCTOR&DESTRUCTOR-----
/** Constructor - dimension gives the size of the vectors to work with. */
VectorAverage ();
/** Destructor */
~VectorAverage () {}
//-----METHODS-----
/** Reset the object to work with a new data set */
inline void
reset ();
/** Get the mean of the added vectors */
inline const
Eigen::Matrix<real, dimension, 1>& getMean () const { return mean_;}
/** Get the covariance matrix of the added vectors */
inline const
Eigen::Matrix<real, dimension, dimension>& getCovariance () const { return covariance_;}
/** Get the summed up weight of all added vectors */
inline real
getAccumulatedWeight () const { return accumulatedWeight_;}
/** Get the number of added vectors */
inline unsigned int
getNoOfSamples () { return noOfSamples_;}
/** Add a new sample */
inline void
add (const Eigen::Matrix<real, dimension, 1>& sample, real weight=1.0);
/** Do Principal component analysis */
inline 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 */
inline void
doPCA (Eigen::Matrix<real, dimension, 1>& eigen_values) const;
/** Get the eigenvector corresponding to the smallest eigenvalue */
inline void
getEigenVector1 (Eigen::Matrix<real, dimension, 1>& eigen_vector1) const;
//-----VARIABLES-----
protected:
//-----METHODS-----
//-----VARIABLES-----
unsigned int noOfSamples_;
real accumulatedWeight_;
Eigen::Matrix<real, dimension, 1> mean_;
Eigen::Matrix<real, dimension, dimension> covariance_;
};
typedef VectorAverage<float, 2> VectorAverage2f;
typedef VectorAverage<float, 3> VectorAverage3f;
typedef VectorAverage<float, 4> VectorAverage4f;
} // END namespace
#include <pcl/common/impl/vector_average.hpp>
#endif // #ifndef PCL_VECTOR_AVERAGE_H
pcl::VectorAverage::getEigenVector1
void getEigenVector1(Eigen::Matrix< real, dimension, 1 > &eigen_vector1) const
Get the eigenvector corresponding to the smallest eigenvalue.
Definition: vector_average.hpp:120
pcl::VectorAverage::getAccumulatedWeight
real getAccumulatedWeight() const
Get the summed up weight of all added vectors.
Definition: vector_average.h:77
pcl
Definition: convolution.h:45
pcl::VectorAverage::reset
void reset()
Reset the object to work with a new data set.
Definition: vector_average.hpp:53
pcl::VectorAverage::VectorAverage
VectorAverage()
Constructor - dimension gives the size of the vectors to work with.
Definition: vector_average.hpp:44
pcl::VectorAverage::add
void add(const Eigen::Matrix< real, dimension, 1 > &sample, real weight=1.0)
Add a new sample.
Definition: vector_average.hpp:62
pcl::VectorAverage::getNoOfSamples
unsigned int getNoOfSamples()
Get the number of added vectors.
Definition: vector_average.h:81
pcl::VectorAverage::accumulatedWeight_
real accumulatedWeight_
Definition: vector_average.h:106
pcl::VectorAverage::~VectorAverage
~VectorAverage()
Destructor.
Definition: vector_average.h:60
pcl::VectorAverage::getMean
const Eigen::Matrix< real, dimension, 1 > & getMean() const
Get the mean of the added vectors.
Definition: vector_average.h:69
pcl::VectorAverage::doPCA
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.
Definition: vector_average.hpp:83
pcl::VectorAverage::mean_
Eigen::Matrix< real, dimension, 1 > mean_
Definition: vector_average.h:107
pcl::VectorAverage::covariance_
Eigen::Matrix< real, dimension, dimension > covariance_
Definition: vector_average.h:108
pcl::VectorAverage4f
VectorAverage< float, 4 > VectorAverage4f
Definition: vector_average.h:113
pcl::VectorAverage::getCovariance
const Eigen::Matrix< real, dimension, dimension > & getCovariance() const
Get the covariance matrix of the added vectors.
Definition: vector_average.h:73
pcl::VectorAverage3f
VectorAverage< float, 3 > VectorAverage3f
Definition: vector_average.h:112
pcl::VectorAverage::noOfSamples_
unsigned int noOfSamples_
Definition: vector_average.h:105
pcl::VectorAverage2f
VectorAverage< float, 2 > VectorAverage2f
Definition: vector_average.h:111
pcl::VectorAverage
Calculates the weighted average and the covariance matrix.
Definition: vector_average.h:53