Point Cloud Library (PCL)  1.12.0-dev
intensity_spin.h
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40 
41 #pragma once
42 
43 #include <pcl/features/feature.h>
44 
45 namespace pcl
46 {
47  /** \brief IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud
48  * dataset containing points and intensity. For more information about the intensity-domain spin image descriptor,
49  * see:
50  *
51  * Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce.
52  * A sparse texture representation using local affine regions.
53  * In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 27, pages 1265-1278, August 2005.
54  * \author Michael Dixon
55  * \ingroup features
56  */
57  template <typename PointInT, typename PointOutT>
58  class IntensitySpinEstimation: public Feature<PointInT, PointOutT>
59  {
60  public:
61  using Ptr = shared_ptr<IntensitySpinEstimation<PointInT, PointOutT> >;
62  using ConstPtr = shared_ptr<const IntensitySpinEstimation<PointInT, PointOutT> >;
65 
69 
72 
75 
76  /** \brief Empty constructor. */
78  {
79  feature_name_ = "IntensitySpinEstimation";
80  };
81 
82  /** \brief Estimate the intensity-domain spin image descriptor for a given point based on its spatial
83  * neighborhood of 3D points and their intensities.
84  * \param[in] cloud the dataset containing the Cartesian coordinates and intensity values of the points
85  * \param[in] radius the radius of the feature
86  * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use during the soft histogram update
87  * \param[in] k the number of neighbors to use from \a indices and \a squared_distances
88  * \param[in] indices the indices of the points that comprise the query point's neighborhood
89  * \param[in] squared_distances the squared distances from the query point to each point in the neighborhood
90  * \param[out] intensity_spin_image the resultant intensity-domain spin image descriptor
91  */
92  void
94  float radius, float sigma, int k,
95  const pcl::Indices &indices,
96  const std::vector<float> &squared_distances,
97  Eigen::MatrixXf &intensity_spin_image);
98 
99  /** \brief Set the number of bins to use in the distance dimension of the spin image
100  * \param[in] nr_distance_bins the number of bins to use in the distance dimension of the spin image
101  */
102  inline void
103  setNrDistanceBins (std::size_t nr_distance_bins) { nr_distance_bins_ = static_cast<int> (nr_distance_bins); };
104 
105  /** \brief Returns the number of bins in the distance dimension of the spin image. */
106  inline int
108 
109  /** \brief Set the number of bins to use in the intensity dimension of the spin image.
110  * \param[in] nr_intensity_bins the number of bins to use in the intensity dimension of the spin image
111  */
112  inline void
113  setNrIntensityBins (std::size_t nr_intensity_bins) { nr_intensity_bins_ = static_cast<int> (nr_intensity_bins); };
114 
115  /** \brief Returns the number of bins in the intensity dimension of the spin image. */
116  inline int
118 
119  /** \brief Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.
120  * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images
121  */
122  inline void
123  setSmoothingBandwith (float sigma) { sigma_ = sigma; };
124 
125  /** \brief Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images. */
126  inline float
127  getSmoothingBandwith () { return (sigma_); };
128 
129 
130  /** \brief Estimate the intensity-domain descriptors at a set of points given by <setInputCloud (), setIndices ()>
131  * using the surface in setSearchSurface (), and the spatial locator in setSearchMethod ().
132  * \param[out] output the resultant point cloud model dataset that contains the intensity-domain spin image features
133  */
134  void
135  computeFeature (PointCloudOut &output) override;
136 
137  /** \brief The number of distance bins in the descriptor. */
139 
140  /** \brief The number of intensity bins in the descriptor. */
142 
143  /** \brief The standard deviation of the Gaussian smoothing kernel used to construct the spin images. */
144  float sigma_;
145  };
146 }
147 
148 #ifdef PCL_NO_PRECOMPILE
149 #include <pcl/features/impl/intensity_spin.hpp>
150 #endif
151 
152 
153 
154 
pcl
Definition: convolution.h:46
pcl::Feature::Ptr
shared_ptr< Feature< PointInT, PointOutT > > Ptr
Definition: feature.h:114
pcl::IntensitySpinEstimation::computeFeature
void computeFeature(PointCloudOut &output) override
Estimate the intensity-domain descriptors at a set of points given by <setInputCloud (),...
Definition: intensity_spin.hpp:110
pcl::IntensitySpinEstimation::getNrIntensityBins
int getNrIntensityBins()
Returns the number of bins in the intensity dimension of the spin image.
Definition: intensity_spin.h:117
pcl::IntensitySpinEstimation::setNrIntensityBins
void setNrIntensityBins(std::size_t nr_intensity_bins)
Set the number of bins to use in the intensity dimension of the spin image.
Definition: intensity_spin.h:113
pcl::IntensitySpinEstimation::IntensitySpinEstimation
IntensitySpinEstimation()
Empty constructor.
Definition: intensity_spin.h:77
pcl::PointCloud< PointInT >
pcl::Feature::ConstPtr
shared_ptr< const Feature< PointInT, PointOutT > > ConstPtr
Definition: feature.h:115
pcl::IntensitySpinEstimation::nr_distance_bins_
int nr_distance_bins_
The number of distance bins in the descriptor.
Definition: intensity_spin.h:138
pcl::IntensitySpinEstimation::PointCloudOut
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: intensity_spin.h:74
pcl::IntensitySpinEstimation
IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud...
Definition: intensity_spin.h:58
pcl::IntensitySpinEstimation::setNrDistanceBins
void setNrDistanceBins(std::size_t nr_distance_bins)
Set the number of bins to use in the distance dimension of the spin image.
Definition: intensity_spin.h:103
pcl::IntensitySpinEstimation::setSmoothingBandwith
void setSmoothingBandwith(float sigma)
Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.
Definition: intensity_spin.h:123
pcl::IntensitySpinEstimation::computeIntensitySpinImage
void computeIntensitySpinImage(const PointCloudIn &cloud, float radius, float sigma, int k, const pcl::Indices &indices, const std::vector< float > &squared_distances, Eigen::MatrixXf &intensity_spin_image)
Estimate the intensity-domain spin image descriptor for a given point based on its spatial neighborho...
Definition: intensity_spin.hpp:48
pcl::IntensitySpinEstimation::PointCloudIn
pcl::PointCloud< PointInT > PointCloudIn
Definition: intensity_spin.h:73
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
pcl::IntensitySpinEstimation::getNrDistanceBins
int getNrDistanceBins()
Returns the number of bins in the distance dimension of the spin image.
Definition: intensity_spin.h:107
pcl::IntensitySpinEstimation::sigma_
float sigma_
The standard deviation of the Gaussian smoothing kernel used to construct the spin images.
Definition: intensity_spin.h:144
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition: feature.h:223
pcl::IntensitySpinEstimation::getSmoothingBandwith
float getSmoothingBandwith()
Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images.
Definition: intensity_spin.h:127
pcl::IntensitySpinEstimation::nr_intensity_bins_
int nr_intensity_bins_
The number of intensity bins in the descriptor.
Definition: intensity_spin.h:141
pcl::Feature
Feature represents the base feature class.
Definition: feature.h:106