FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals. More...
#include <pcl/features/fpfh.h>
Public Member Functions |
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| FPFHEstimation () | |
| Empty constructor. More... |
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| 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 represented by Cartesian coordinates and normals. More... |
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| void | computePointSPFHSignature (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, pcl::index_t p_idx, int row, const pcl::Indices &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, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals. More... |
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| void | weightPointSPFHSignature (const Eigen::MatrixXf &hist_f1, const Eigen::MatrixXf &hist_f2, const Eigen::MatrixXf &hist_f3, const pcl::Indices &indices, const std::vector< float > &dists, Eigen::VectorXf &fpfh_histogram) |
| Weight the SPFH (Simple Point Feature Histograms) individual histograms to create the final FPFH (Fast Point Feature Histogram) for a given point based on its 3D spatial neighborhood. More... |
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| void | setNrSubdivisions (int nr_bins_f1, int nr_bins_f2, int nr_bins_f3) |
| Set the number of subdivisions for each angular feature interval. More... |
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| void | getNrSubdivisions (int &nr_bins_f1, int &nr_bins_f2, int &nr_bins_f3) |
| Get the number of subdivisions for each angular feature interval. More... |
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 Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > |
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| FeatureFromNormals () | |
| Empty constructor. More... |
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| virtual | ~FeatureFromNormals () |
| Empty destructor. More... |
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| void | setInputNormals (const PointCloudNConstPtr &normals) |
| Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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| PointCloudNConstPtr | getInputNormals () const |
| Get a pointer to the normals of the input XYZ point cloud dataset. More... |
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| Public Member Functions inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 > |
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| Feature () | |
| Empty constructor. More... |
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| virtual | ~Feature () |
| Empty destructor. More... |
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| void | setSearchSurface (const PointCloudInConstPtr &cloud) |
| Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More... |
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| PointCloudInConstPtr | getSearchSurface () const |
| Get a pointer to the surface point cloud dataset. More... |
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| void | setSearchMethod (const KdTreePtr &tree) |
| Provide a pointer to the search object. More... |
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| KdTreePtr | getSearchMethod () const |
| Get a pointer to the search method used. More... |
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| double | getSearchParameter () const |
| Get the internal search parameter. More... |
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| void | setKSearch (int k) |
| Set the number of k nearest neighbors to use for the feature estimation. More... |
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| int | getKSearch () const |
| get the number of k nearest neighbors used for the feature estimation. More... |
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| void | setRadiusSearch (double radius) |
| Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More... |
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| double | getRadiusSearch () const |
| Get the sphere radius used for determining the neighbors. More... |
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| void | compute (PointCloudOut &output) |
| Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More... |
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| Public Member Functions inherited from pcl::PCLBase< PointInT > |
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| PCLBase () | |
| Empty constructor. More... |
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| PCLBase (const PCLBase &base) | |
| Copy constructor. More... |
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| virtual | ~PCLBase ()=default |
| Destructor. More... |
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| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... |
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| const PointCloudConstPtr | getInputCloud () const |
| Get a pointer to the input point cloud dataset. More... |
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| virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud. More... |
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| IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used. More... |
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| const IndicesConstPtr | getIndices () const |
| Get a pointer to the vector of indices used. More... |
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| const PointInT & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code. More... |
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Protected Member Functions |
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| 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. More... |
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| void | computeFeature (PointCloudOut &output) override |
| Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More... |
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| Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > |
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| virtual bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| Protected Member Functions inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 > |
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| const std::string & | getClassName () const |
| Get a string representation of the name of this class. More... |
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| virtual bool | deinitCompute () |
| This method should get called after ending the actual computation. More... |
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| int | searchForNeighbors (std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const |
| Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More... |
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| int | searchForNeighbors (const PointCloudIn &cloud, std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const |
| Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More... |
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| Protected Member Functions inherited from pcl::PCLBase< PointInT > |
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| bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| bool | deinitCompute () |
| This method should get called after finishing the actual computation. More... |
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Protected Attributes |
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| int | nr_bins_f1_ |
| The number of subdivisions for each angular feature interval. More... |
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| int | nr_bins_f2_ |
| int | nr_bins_f3_ |
| Eigen::MatrixXf | hist_f1_ |
| Placeholder for the f1 histogram. More... |
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| Eigen::MatrixXf | hist_f2_ |
| Placeholder for the f2 histogram. More... |
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| Eigen::MatrixXf | hist_f3_ |
| Placeholder for the f3 histogram. More... |
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| Eigen::VectorXf | fpfh_histogram_ |
| Placeholder for a point's FPFH signature. More... |
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| float | d_pi_ |
| Float constant = 1.0 / (2.0 * M_PI) More... |
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| Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > |
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| PointCloudNConstPtr | normals_ |
| A pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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| Protected Attributes inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 > |
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| std::string | feature_name_ |
| The feature name. More... |
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| SearchMethodSurface | search_method_surface_ |
| The search method template for points. More... |
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| PointCloudInConstPtr | surface_ |
| An input point cloud describing the surface that is to be used for nearest neighbors estimation. More... |
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| KdTreePtr | tree_ |
| A pointer to the spatial search object. More... |
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| double | search_parameter_ |
| The actual search parameter (from either search_radius_ or k_). More... |
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| double | search_radius_ |
| The nearest neighbors search radius for each point. More... |
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| int | k_ |
| The number of K nearest neighbors to use for each point. More... |
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| bool | fake_surface_ |
| If no surface is given, we use the input PointCloud as the surface. More... |
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| Protected Attributes inherited from pcl::PCLBase< PointInT > |
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| PointCloudConstPtr | input_ |
| The input point cloud dataset. More... |
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| IndicesPtr | indices_ |
| A pointer to the vector of point indices to use. More... |
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| bool | use_indices_ |
| Set to true if point indices are used. More... |
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| bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... |
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Detailed Description
template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>
class pcl::FPFHEstimation< PointInT, PointNT, PointOutT >
FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals.
A commonly used type for PointOutT is pcl::FPFHSignature33.
- Note
- If you use this code in any academic work, please cite:
- R.B. Rusu, N. Blodow, M. Beetz. Fast Point Feature Histograms (FPFH) for 3D Registration. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, May 12-17 2009.
- R.B. Rusu, A. Holzbach, N. Blodow, M. Beetz. Fast Geometric Point Labeling using Conditional Random Fields. In Proceedings of the 22nd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, MO, USA, October 11-15 2009.
- Attention
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The convention for FPFH features is:
- if a query point's nearest neighbors cannot be estimated, the FPFH feature will be set to NaN (not a number)
- it is impossible to estimate a FPFH descriptor for a point that doesn't have finite 3D coordinates. Therefore, any point that contains NaN data on x, y, or z, will have its FPFH feature property set to NaN.
- Note
- The code is stateful as we do not expect this class to be multicore parallelized. Please look at FPFHEstimationOMP for examples on parallel implementations of the FPFH (Fast Point Feature Histogram).
Member Typedef Documentation
ConstPtr
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
| using pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const FPFHEstimation<PointInT, PointNT, PointOutT> > |
PointCloudOut
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
| using pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut |
Ptr
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
| using pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<FPFHEstimation<PointInT, PointNT, PointOutT> > |
Constructor & Destructor Documentation
FPFHEstimation()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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inline |
Empty constructor.
Definition at line 95 of file fpfh.h.
References pcl::Feature< PointInT, pcl::FPFHSignature33 >::feature_name_.
Member Function Documentation
computeFeature()
template<typename PointInT , typename PointNT , typename PointOutT >
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overrideprotected |
Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
- Parameters
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[out] output the resultant point cloud model dataset that contains the FPFH feature estimates
Definition at line 238 of file fpfh.hpp.
References pcl::isFinite().
computePairFeatures()
template<typename PointInT , typename PointNT , typename PointOutT >
| bool pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::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 represented by Cartesian coordinates and normals.
- Note
- For explanations about the features, please see the literature mentioned above (the order of the features might be different).
- Parameters
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[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points [in] normals the dataset containing the surface normals (assuming normalized vectors) at each point in cloud [in] p_idx the index of the first point (source) [in] q_idx the index of the second point (target) [out] f1 the first angular feature (angle between the projection of nq_idx and u) [out] f2 the second angular feature (angle between nq_idx and v) [out] f3 the third angular feature (angle between np_idx and |p_idx - q_idx|) [out] f4 the distance feature (p_idx - q_idx)
Definition at line 52 of file fpfh.hpp.
References pcl::computePairFeatures().
computePointSPFHSignature()
template<typename PointInT , typename PointNT , typename PointOutT >
| void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computePointSPFHSignature | ( | const pcl::PointCloud< PointInT > & | cloud, |
| const pcl::PointCloud< PointNT > & | normals, | ||
| pcl::index_t | p_idx, | ||
| int | row, | ||
| const pcl::Indices & | 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, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals.
- Parameters
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[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points [in] normals the dataset containing the surface normals at each point in cloud [in] p_idx the index of the query point (source) [in] row the index row in feature histogramms [in] indices the k-neighborhood point indices in the dataset [out] hist_f1 the resultant SPFH histogram for feature f1 [out] hist_f2 the resultant SPFH histogram for feature f2 [out] hist_f3 the resultant SPFH histogram for feature f3
Definition at line 64 of file fpfh.hpp.
References pcl::computePairFeatures(), and M_PI.
computeSPFHSignatures()
template<typename PointInT , typename PointNT , typename PointOutT >
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protected |
Estimate the set of all SPFH (Simple Point Feature Histograms) signatures for the input cloud.
- Parameters
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[out] spf_hist_lookup a lookup table for all the SPF feature indices [out] hist_f1 the resultant SPFH histogram for feature f1 [out] hist_f2 the resultant SPFH histogram for feature f2 [out] hist_f3 the resultant SPFH histogram for feature f3
getNrSubdivisions()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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inline |
Get the number of subdivisions for each angular feature interval.
- Parameters
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[out] nr_bins_f1 number of subdivisions for the first angular feature [out] nr_bins_f2 number of subdivisions for the second angular feature [out] nr_bins_f3 number of subdivisions for the third angular feature
Definition at line 172 of file fpfh.h.
References pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f1_, pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f2_, and pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f3_.
setNrSubdivisions()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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inline |
Set the number of subdivisions for each angular feature interval.
- Parameters
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[in] nr_bins_f1 number of subdivisions for the first angular feature [in] nr_bins_f2 number of subdivisions for the second angular feature [in] nr_bins_f3 number of subdivisions for the third angular feature
Definition at line 159 of file fpfh.h.
References pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f1_, pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f2_, and pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f3_.
weightPointSPFHSignature()
template<typename PointInT , typename PointNT , typename PointOutT >
| void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::weightPointSPFHSignature | ( | const Eigen::MatrixXf & | hist_f1, |
| const Eigen::MatrixXf & | hist_f2, | ||
| const Eigen::MatrixXf & | hist_f3, | ||
| const pcl::Indices & | indices, | ||
| const std::vector< float > & | dists, | ||
| Eigen::VectorXf & | fpfh_histogram | ||
| ) |
Weight the SPFH (Simple Point Feature Histograms) individual histograms to create the final FPFH (Fast Point Feature Histogram) for a given point based on its 3D spatial neighborhood.
- Parameters
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[in] hist_f1 the histogram feature vector of f1 values over the given patch [in] hist_f2 the histogram feature vector of f2 values over the given patch [in] hist_f3 the histogram feature vector of f3 values over the given patch [in] indices the point indices of p_idx's k-neighborhood in the point cloud [in] dists the distances from p_idx to all its k-neighbors [out] fpfh_histogram the resultant FPFH histogram representing the feature at the query point
Member Data Documentation
d_pi_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
fpfh_histogram_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
hist_f1_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
hist_f2_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
hist_f3_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
nr_bins_f1_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
The number of subdivisions for each angular feature interval.
Definition at line 200 of file fpfh.h.
Referenced by pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::getNrSubdivisions(), and pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::setNrSubdivisions().
nr_bins_f2_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
Definition at line 200 of file fpfh.h.
Referenced by pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::getNrSubdivisions(), and pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::setNrSubdivisions().
nr_bins_f3_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
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protected |
Definition at line 200 of file fpfh.h.
Referenced by pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::getNrSubdivisions(), and pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::setNrSubdivisions().
The documentation for this class was generated from the following files:
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_f_p_f_h_estimation.html
