Point Cloud Library (PCL)  1.9.1-dev
fpfh.h
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40 
41 #pragma once
42 
43 #include <pcl/features/feature.h>
44 #include <set>
45 
46 namespace pcl
47 {
48  /** \brief FPFHEstimation estimates the <b>Fast Point Feature Histogram (FPFH)</b> descriptor for a given point
49  * cloud dataset containing points and normals.
50  *
51  * A commonly used type for PointOutT is pcl::FPFHSignature33.
52  *
53  * \note If you use this code in any academic work, please cite:
54  *
55  * - R.B. Rusu, N. Blodow, M. Beetz.
56  * Fast Point Feature Histograms (FPFH) for 3D Registration.
57  * In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),
58  * Kobe, Japan, May 12-17 2009.
59  * - R.B. Rusu, A. Holzbach, N. Blodow, M. Beetz.
60  * Fast Geometric Point Labeling using Conditional Random Fields.
61  * In Proceedings of the 22nd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
62  * St. Louis, MO, USA, October 11-15 2009.
63  *
64  * \attention
65  * The convention for FPFH features is:
66  * - if a query point's nearest neighbors cannot be estimated, the FPFH feature will be set to NaN
67  * (not a number)
68  * - it is impossible to estimate a FPFH descriptor for a point that
69  * doesn't have finite 3D coordinates. Therefore, any point that contains
70  * NaN data on x, y, or z, will have its FPFH feature property set to NaN.
71  *
72  * \note The code is stateful as we do not expect this class to be multicore parallelized. Please look at
73  * \ref FPFHEstimationOMP for examples on parallel implementations of the FPFH (Fast Point Feature Histogram).
74  *
75  * \author Radu B. Rusu
76  * \ingroup features
77  */
78  template <typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>
79  class FPFHEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT>
80  {
81  public:
82  typedef boost::shared_ptr<FPFHEstimation<PointInT, PointNT, PointOutT> > Ptr;
83  typedef boost::shared_ptr<const FPFHEstimation<PointInT, PointNT, PointOutT> > ConstPtr;
92 
94 
95  /** \brief Empty constructor. */
97  nr_bins_f1_ (11), nr_bins_f2_ (11), nr_bins_f3_ (11),
98  d_pi_ (1.0f / (2.0f * static_cast<float> (M_PI)))
99  {
100  feature_name_ = "FPFHEstimation";
101  };
102 
103  /** \brief Compute the 4-tuple representation containing the three angles and one distance between two points
104  * represented by Cartesian coordinates and normals.
105  * \note For explanations about the features, please see the literature mentioned above (the order of the
106  * features might be different).
107  * \param[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points
108  * \param[in] normals the dataset containing the surface normals (assuming normalized vectors) at each point in cloud
109  * \param[in] p_idx the index of the first point (source)
110  * \param[in] q_idx the index of the second point (target)
111  * \param[out] f1 the first angular feature (angle between the projection of nq_idx and u)
112  * \param[out] f2 the second angular feature (angle between nq_idx and v)
113  * \param[out] f3 the third angular feature (angle between np_idx and |p_idx - q_idx|)
114  * \param[out] f4 the distance feature (p_idx - q_idx)
115  */
116  bool
118  int p_idx, int q_idx, float &f1, float &f2, float &f3, float &f4);
119 
120  /** \brief Estimate the SPFH (Simple Point Feature Histograms) individual signatures of the three angular
121  * (f1, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals
122  * \param[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points
123  * \param[in] normals the dataset containing the surface normals at each point in \a cloud
124  * \param[in] p_idx the index of the query point (source)
125  * \param[in] row the index row in feature histogramms
126  * \param[in] indices the k-neighborhood point indices in the dataset
127  * \param[out] hist_f1 the resultant SPFH histogram for feature f1
128  * \param[out] hist_f2 the resultant SPFH histogram for feature f2
129  * \param[out] hist_f3 the resultant SPFH histogram for feature f3
130  */
131  void
133  const pcl::PointCloud<PointNT> &normals, int p_idx, int row,
134  const std::vector<int> &indices,
135  Eigen::MatrixXf &hist_f1, Eigen::MatrixXf &hist_f2, Eigen::MatrixXf &hist_f3);
136 
137  /** \brief Weight the SPFH (Simple Point Feature Histograms) individual histograms to create the final FPFH
138  * (Fast Point Feature Histogram) for a given point based on its 3D spatial neighborhood
139  * \param[in] hist_f1 the histogram feature vector of \a f1 values over the given patch
140  * \param[in] hist_f2 the histogram feature vector of \a f2 values over the given patch
141  * \param[in] hist_f3 the histogram feature vector of \a f3 values over the given patch
142  * \param[in] indices the point indices of p_idx's k-neighborhood in the point cloud
143  * \param[in] dists the distances from p_idx to all its k-neighbors
144  * \param[out] fpfh_histogram the resultant FPFH histogram representing the feature at the query point
145  */
146  void
147  weightPointSPFHSignature (const Eigen::MatrixXf &hist_f1,
148  const Eigen::MatrixXf &hist_f2,
149  const Eigen::MatrixXf &hist_f3,
150  const std::vector<int> &indices,
151  const std::vector<float> &dists,
152  Eigen::VectorXf &fpfh_histogram);
153 
154  /** \brief Set the number of subdivisions for each angular feature interval.
155  * \param[in] nr_bins_f1 number of subdivisions for the first angular feature
156  * \param[in] nr_bins_f2 number of subdivisions for the second angular feature
157  * \param[in] nr_bins_f3 number of subdivisions for the third angular feature
158  */
159  inline void
160  setNrSubdivisions (int nr_bins_f1, int nr_bins_f2, int nr_bins_f3)
161  {
162  nr_bins_f1_ = nr_bins_f1;
163  nr_bins_f2_ = nr_bins_f2;
164  nr_bins_f3_ = nr_bins_f3;
165  }
166 
167  /** \brief Get the number of subdivisions for each angular feature interval.
168  * \param[out] nr_bins_f1 number of subdivisions for the first angular feature
169  * \param[out] nr_bins_f2 number of subdivisions for the second angular feature
170  * \param[out] nr_bins_f3 number of subdivisions for the third angular feature
171  */
172  inline void
173  getNrSubdivisions (int &nr_bins_f1, int &nr_bins_f2, int &nr_bins_f3)
174  {
175  nr_bins_f1 = nr_bins_f1_;
176  nr_bins_f2 = nr_bins_f2_;
177  nr_bins_f3 = nr_bins_f3_;
178  }
179 
180  protected:
181 
182  /** \brief Estimate the set of all SPFH (Simple Point Feature Histograms) signatures for the input cloud
183  * \param[out] spf_hist_lookup a lookup table for all the SPF feature indices
184  * \param[out] hist_f1 the resultant SPFH histogram for feature f1
185  * \param[out] hist_f2 the resultant SPFH histogram for feature f2
186  * \param[out] hist_f3 the resultant SPFH histogram for feature f3
187  */
188  void
189  computeSPFHSignatures (std::vector<int> &spf_hist_lookup,
190  Eigen::MatrixXf &hist_f1, Eigen::MatrixXf &hist_f2, Eigen::MatrixXf &hist_f3);
191 
192  /** \brief Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by
193  * <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
194  * setSearchMethod ()
195  * \param[out] output the resultant point cloud model dataset that contains the FPFH feature estimates
196  */
197  void
198  computeFeature (PointCloudOut &output) override;
199 
200  /** \brief The number of subdivisions for each angular feature interval. */
202 
203  /** \brief Placeholder for the f1 histogram. */
204  Eigen::MatrixXf hist_f1_;
205 
206  /** \brief Placeholder for the f2 histogram. */
207  Eigen::MatrixXf hist_f2_;
208 
209  /** \brief Placeholder for the f3 histogram. */
210  Eigen::MatrixXf hist_f3_;
211 
212  /** \brief Placeholder for a point's FPFH signature. */
213  Eigen::VectorXf fpfh_histogram_;
214 
215  /** \brief Float constant = 1.0 / (2.0 * M_PI) */
216  float d_pi_;
217  };
218 }
219 
220 #ifdef PCL_NO_PRECOMPILE
221 #include <pcl/features/impl/fpfh.hpp>
222 #endif
Eigen::MatrixXf hist_f1_
Placeholder for the f1 histogram.
Definition: fpfh.h:204
void computeSPFHSignatures(std::vector< int > &spf_hist_lookup, Eigen::MatrixXf &hist_f1, Eigen::MatrixXf &hist_f2, Eigen::MatrixXf &hist_f3)
Estimate the set of all SPFH (Simple Point Feature Histograms) signatures for the input cloud...
Definition: fpfh.hpp:174
float d_pi_
Float constant = 1.0 / (2.0 * M_PI)
Definition: fpfh.h:216
int nr_bins_f1_
The number of subdivisions for each angular feature interval.
Definition: fpfh.h:201
void getNrSubdivisions(int &nr_bins_f1, int &nr_bins_f2, int &nr_bins_f3)
Get the number of subdivisions for each angular feature interval.
Definition: fpfh.h:173
std::string feature_name_
The feature name.
Definition: feature.h:221
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:44
void computeFeature(PointCloudOut &output) override
Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by <setInputCl...
Definition: fpfh.hpp:234
void setNrSubdivisions(int nr_bins_f1, int nr_bins_f2, int nr_bins_f3)
Set the number of subdivisions for each angular feature interval.
Definition: fpfh.h:160
Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: fpfh.h:93
boost::shared_ptr< FPFHEstimation< PointInT, PointNT, PointOutT > > Ptr
Definition: fpfh.h:82
void weightPointSPFHSignature(const Eigen::MatrixXf &hist_f1, const Eigen::MatrixXf &hist_f2, const Eigen::MatrixXf &hist_f3, const std::vector< int > &indices, const std::vector< float > &dists, Eigen::VectorXf &fpfh_histogram)
Weight the SPFH (Simple Point Feature Histograms) individual histograms to create the final FPFH (Fas...
Definition: fpfh.hpp:106
Eigen::MatrixXf hist_f2_
Placeholder for the f2 histogram.
Definition: fpfh.h:207
FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud d...
Definition: fpfh.h:79
Eigen::VectorXf fpfh_histogram_
Placeholder for a point&#39;s FPFH signature.
Definition: fpfh.h:213
bool computePairFeatures(const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, int p_idx, int q_idx, float &f1, float &f2, float &f3, float &f4)
Compute the 4-tuple representation containing the three angles and one distance between two points re...
Definition: fpfh.hpp:49
Eigen::MatrixXf hist_f3_
Placeholder for the f3 histogram.
Definition: fpfh.h:210
FPFHEstimation()
Empty constructor.
Definition: fpfh.h:96
void computePointSPFHSignature(const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, int p_idx, int row, const std::vector< int > &indices, Eigen::MatrixXf &hist_f1, Eigen::MatrixXf &hist_f2, Eigen::MatrixXf &hist_f3)
Estimate the SPFH (Simple Point Feature Histograms) individual signatures of the three angular (f1...
Definition: fpfh.hpp:61
boost::shared_ptr< const FPFHEstimation< PointInT, PointNT, PointOutT > > ConstPtr
Definition: fpfh.h:83
Feature represents the base feature class.
Definition: feature.h:104