W3cubDocs

/PointCloudLibrary

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 Types

using Ptr = shared_ptr< FPFHEstimation< PointInT, PointNT, PointOutT > >
using ConstPtr = shared_ptr< const FPFHEstimation< PointInT, PointNT, PointOutT > >
using PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut
- Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >
using PointCloudN = pcl::PointCloud< PointNT >
using PointCloudNPtr = typename PointCloudN::Ptr
using PointCloudNConstPtr = typename PointCloudN::ConstPtr
using Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > >
using ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > >
- Public Types inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 >
using BaseClass = PCLBase< PointInT >
using Ptr = shared_ptr< Feature< PointInT, pcl::FPFHSignature33 > >
using ConstPtr = shared_ptr< const Feature< PointInT, pcl::FPFHSignature33 > >
using KdTree = pcl::search::Search< PointInT >
using KdTreePtr = typename KdTree::Ptr
using PointCloudIn = pcl::PointCloud< PointInT >
using PointCloudInPtr = typename PointCloudIn::Ptr
using PointCloudInConstPtr = typename PointCloudIn::ConstPtr
using PointCloudOut = pcl::PointCloud< pcl::FPFHSignature33 >
using SearchMethod = std::function< int(std::size_t, double, pcl::Indices &, std::vector< float > &)>
using SearchMethodSurface = std::function< int(const PointCloudIn &cloud, std::size_t index, double, pcl::Indices &, std::vector< float > &)>
- Public Types inherited from pcl::PCLBase< PointInT >
using PointCloud = pcl::PointCloud< PointInT >
using PointCloudPtr = typename PointCloud::Ptr
using PointCloudConstPtr = typename PointCloud::ConstPtr
using PointIndicesPtr = PointIndices::Ptr
using PointIndicesConstPtr = PointIndices::ConstPtr

Public Member Functions

FPFHEstimation ()
Empty constructor. More...
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...
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...
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...
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...
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...
- Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >
FeatureFromNormals ()
Empty constructor. More...
virtual ~FeatureFromNormals ()
Empty destructor. More...
void setInputNormals (const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More...
PointCloudNConstPtr getInputNormals () const
Get a pointer to the normals of the input XYZ point cloud dataset. More...
- Public Member Functions inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 >
Feature ()
Empty constructor. More...
virtual ~Feature ()
Empty destructor. More...
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...
PointCloudInConstPtr getSearchSurface () const
Get a pointer to the surface point cloud dataset. More...
void setSearchMethod (const KdTreePtr &tree)
Provide a pointer to the search object. More...
KdTreePtr getSearchMethod () const
Get a pointer to the search method used. More...
double getSearchParameter () const
Get the internal search parameter. More...
void setKSearch (int k)
Set the number of k nearest neighbors to use for the feature estimation. More...
int getKSearch () const
get the number of k nearest neighbors used for the feature estimation. More...
void setRadiusSearch (double radius)
Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More...
double getRadiusSearch () const
Get the sphere radius used for determining the neighbors. More...
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...
- Public Member Functions inherited from pcl::PCLBase< PointInT >
PCLBase ()
Empty constructor. More...
PCLBase (const PCLBase &base)
Copy constructor. More...
virtual ~PCLBase ()=default
Destructor. More...
virtual void setInputCloud (const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset. More...
const PointCloudConstPtr getInputCloud () const
Get a pointer to the input point cloud dataset. More...
virtual void setIndices (const IndicesPtr &indices)
Provide a pointer to the vector of indices that represents the input data. More...
virtual void setIndices (const IndicesConstPtr &indices)
Provide a pointer to the vector of indices that represents the input data. More...
virtual void setIndices (const PointIndicesConstPtr &indices)
Provide a pointer to the vector of indices that represents the input data. More...
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...
IndicesPtr getIndices ()
Get a pointer to the vector of indices used. More...
const IndicesConstPtr getIndices () const
Get a pointer to the vector of indices used. More...
const PointInT & operator[] (std::size_t pos) const
Override PointCloud operator[] to shorten code. More...

Protected Member Functions

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...
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...
- Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >
virtual bool initCompute ()
This method should get called before starting the actual computation. More...
- Protected Member Functions inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 >
const std::string & getClassName () const
Get a string representation of the name of this class. More...
virtual bool deinitCompute ()
This method should get called after ending the actual computation. More...
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...
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...
- Protected Member Functions inherited from pcl::PCLBase< PointInT >
bool initCompute ()
This method should get called before starting the actual computation. More...
bool deinitCompute ()
This method should get called after finishing the actual computation. More...

Protected Attributes

int nr_bins_f1_
The number of subdivisions for each angular feature interval. More...
int nr_bins_f2_
int nr_bins_f3_
Eigen::MatrixXf hist_f1_
Placeholder for the f1 histogram. More...
Eigen::MatrixXf hist_f2_
Placeholder for the f2 histogram. More...
Eigen::MatrixXf hist_f3_
Placeholder for the f3 histogram. More...
Eigen::VectorXf fpfh_histogram_
Placeholder for a point's FPFH signature. More...
float d_pi_
Float constant = 1.0 / (2.0 * M_PI) More...
- Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset. More...
- Protected Attributes inherited from pcl::Feature< PointInT, pcl::FPFHSignature33 >
std::string feature_name_
The feature name. More...
SearchMethodSurface search_method_surface_
The search method template for points. More...
PointCloudInConstPtr surface_
An input point cloud describing the surface that is to be used for nearest neighbors estimation. More...
KdTreePtr tree_
A pointer to the spatial search object. More...
double search_parameter_
The actual search parameter (from either search_radius_ or k_). More...
double search_radius_
The nearest neighbors search radius for each point. More...
int k_
The number of K nearest neighbors to use for each point. More...
bool fake_surface_
If no surface is given, we use the input PointCloud as the surface. More...
- Protected Attributes inherited from pcl::PCLBase< PointInT >
PointCloudConstPtr input_
The input point cloud dataset. More...
IndicesPtr indices_
A pointer to the vector of point indices to use. More...
bool use_indices_
Set to true if point indices are used. More...
bool fake_indices_
If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...

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
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).
Author
Radu B. Rusu

Definition at line 78 of file fpfh.h.

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> >

Definition at line 82 of file fpfh.h.

PointCloudOut

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
using pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 92 of file fpfh.h.

Ptr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
using pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<FPFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 81 of file fpfh.h.

Constructor & Destructor Documentation

FPFHEstimation()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::FPFHEstimation ( )
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 >
void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature ( PointCloudOut & output )
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
[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
[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
[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 >
void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeSPFHSignatures ( std::vector< int > & spf_hist_lookup,
Eigen::MatrixXf & hist_f1,
Eigen::MatrixXf & hist_f2,
Eigen::MatrixXf & hist_f3
)
protected

Estimate the set of all SPFH (Simple Point Feature Histograms) signatures for the input cloud.

Parameters
[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

Definition at line 182 of file fpfh.hpp.

getNrSubdivisions()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::getNrSubdivisions ( int & nr_bins_f1,
int & nr_bins_f2,
int & nr_bins_f3
)
inline

Get the number of subdivisions for each angular feature interval.

Parameters
[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>
void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::setNrSubdivisions ( int nr_bins_f1,
int nr_bins_f2,
int nr_bins_f3
)
inline

Set the number of subdivisions for each angular feature interval.

Parameters
[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
[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

Definition at line 110 of file fpfh.hpp.

Member Data Documentation

d_pi_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
float pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::d_pi_
protected

Float constant = 1.0 / (2.0 * M_PI)

Definition at line 215 of file fpfh.h.

fpfh_histogram_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
Eigen::VectorXf pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::fpfh_histogram_
protected

Placeholder for a point's FPFH signature.

Definition at line 212 of file fpfh.h.

hist_f1_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
Eigen::MatrixXf pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f1_
protected

Placeholder for the f1 histogram.

Definition at line 203 of file fpfh.h.

hist_f2_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
Eigen::MatrixXf pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f2_
protected

Placeholder for the f2 histogram.

Definition at line 206 of file fpfh.h.

hist_f3_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
Eigen::MatrixXf pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::hist_f3_
protected

Placeholder for the f3 histogram.

Definition at line 209 of file fpfh.h.

nr_bins_f1_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
int pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f1_
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>
int pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f2_
protected

nr_bins_f3_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::FPFHSignature33>
int pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f3_
protected

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