Point Cloud Library (PCL)  1.11.1
vector_average.h
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37 
38 #pragma once
39 
40 #include <pcl/memory.h>
41 #include <pcl/pcl_macros.h>
42 #include <pcl/common/eigen.h>
43 
44 namespace pcl
45 {
46  /** \brief Calculates the weighted average and the covariance matrix
47  *
48  * A class to calculate the weighted average and the covariance matrix of a set of vectors with given weights.
49  * The original data is not saved. Mean and covariance are calculated iteratively.
50  * \author Bastian Steder
51  * \ingroup common
52  */
53  template <typename real, int dimension>
55  {
56  public:
57  using VectorType = Eigen::Matrix<real, dimension, 1>;
58  using MatrixType = Eigen::Matrix<real, dimension, dimension>;
59  //-----CONSTRUCTOR&DESTRUCTOR-----
60  /** Constructor - dimension gives the size of the vectors to work with. */
61  VectorAverage ();
62 
63  //-----METHODS-----
64  /** Reset the object to work with a new data set */
65  inline void
66  reset ();
67 
68  /** Get the mean of the added vectors */
69  inline const
70  VectorType& getMean () const { return mean_;}
71 
72  /** Get the covariance matrix of the added vectors */
73  inline const
74  MatrixType& getCovariance () const { return covariance_;}
75 
76  /** Get the summed up weight of all added vectors */
77  inline real
79 
80  /** Get the number of added vectors */
81  inline unsigned int
83 
84  /** Add a new sample */
85  inline void
86  add (const VectorType& sample, real weight=1.0);
87 
88  /** Do Principal component analysis */
89  inline void
90  doPCA (VectorType& eigen_values, VectorType& eigen_vector1,
91  VectorType& eigen_vector2, VectorType& eigen_vector3) const;
92 
93  /** Do Principal component analysis */
94  inline void
95  doPCA (VectorType& eigen_values) const;
96 
97  /** Get the eigenvector corresponding to the smallest eigenvalue */
98  inline void
99  getEigenVector1 (VectorType& eigen_vector1) const;
100 
102 
103  //-----VARIABLES-----
104 
105 
106  protected:
107  //-----METHODS-----
108  //-----VARIABLES-----
109  unsigned int noOfSamples_ = 0;
111  VectorType mean_ = VectorType::Identity ();
112  MatrixType covariance_ = MatrixType::Identity ();
113  };
114 
118 } // END namespace
119 
120 #include <pcl/common/impl/vector_average.hpp>
pcl::VectorAverage::getAccumulatedWeight
real getAccumulatedWeight() const
Get the summed up weight of all added vectors.
Definition: vector_average.h:78
pcl_macros.h
Defines all the PCL and non-PCL macros used.
pcl
Definition: convolution.h:46
pcl::VectorAverage::getEigenVector1
void getEigenVector1(VectorType &eigen_vector1) const
Get the eigenvector corresponding to the smallest eigenvalue.
Definition: vector_average.hpp:119
pcl::VectorAverage::getCovariance
const MatrixType & getCovariance() const
Get the covariance matrix of the added vectors.
Definition: vector_average.h:74
pcl::VectorAverage::getMean
const VectorType & getMean() const
Get the mean of the added vectors.
Definition: vector_average.h:70
pcl::VectorAverage::VectorAverage
VectorAverage()
Constructor - dimension gives the size of the vectors to work with.
Definition: vector_average.hpp:46
pcl::VectorAverage::mean_
VectorType mean_
Definition: vector_average.h:111
pcl::VectorAverage::VectorType
Eigen::Matrix< real, dimension, 1 > VectorType
Definition: vector_average.h:57
pcl::VectorAverage::accumulatedWeight_
real accumulatedWeight_
Definition: vector_average.h:110
pcl::VectorAverage::reset
void reset()
Reset the object to work with a new data set.
Definition: vector_average.hpp:52
pcl::VectorAverage::getNoOfSamples
unsigned int getNoOfSamples()
Get the number of added vectors.
Definition: vector_average.h:82
pcl::VectorAverage::doPCA
void doPCA(VectorType &eigen_values, VectorType &eigen_vector1, VectorType &eigen_vector2, VectorType &eigen_vector3) const
Do Principal component analysis.
Definition: vector_average.hpp:82
PCL_MAKE_ALIGNED_OPERATOR_NEW
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:63
pcl::VectorAverage
Calculates the weighted average and the covariance matrix.
Definition: vector_average.h:55
pcl::VectorAverage::covariance_
MatrixType covariance_
Definition: vector_average.h:112
pcl::VectorAverage::noOfSamples_
unsigned int noOfSamples_
Definition: vector_average.h:109
pcl::VectorAverage::add
void add(const VectorType &sample, real weight=1.0)
Add a new sample.
Definition: vector_average.hpp:61
pcl::VectorAverage::MatrixType
Eigen::Matrix< real, dimension, dimension > MatrixType
Definition: vector_average.h:58
memory.h
Defines functions, macros and traits for allocating and using memory.