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>

Inheritance diagram for pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >:

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Collaboration diagram for pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >:

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List of all members.

Public Types
typedef Feature< PointInT, pcl::FPFHSignature33 > ::PointCloudOut	PointCloudOut
typedef pcl::PointCloud< PointNT >	PointCloudN
typedef PointCloudN::Ptr	PointCloudNPtr
typedef PointCloudN::ConstPtr	PointCloudNConstPtr
typedef boost::shared_ptr < FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 > >	Ptr
typedef boost::shared_ptr < const FeatureFromNormals < PointInT, PointNT, pcl::FPFHSignature33 > >	ConstPtr
typedef PCLBase< PointInT >	BaseClass
typedef pcl::search::Search < PointInT >	KdTree
typedef pcl::search::Search < PointInT >::Ptr	KdTreePtr
typedef boost::function< int(size_t, double, std::vector< int > &, std::vector< float > &)>	SearchMethod
typedef boost::function< int(const PointCloudIn &cloud, size_t index, double, std::vector < int > &, std::vector< float > &)>	SearchMethodSurface
typedef pcl::PointCloud< PointInT >	PointCloud
typedef PointCloud::Ptr	PointCloudPtr
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef PointIndices::Ptr	PointIndicesPtr
typedef PointIndices::ConstPtr	PointIndicesConstPtr
Public Member Functions
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.
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, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals.
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 (Fast Point Feature Histogram) for a given point based on its 3D spatial neighborhood.
void	setNrSubdivisions (int nr_bins_f1, int nr_bins_f2, int nr_bins_f3)
	Set the number of subdivisions for each angular feature interval.
void	getNrSubdivisions (int &nr_bins_f1, int &nr_bins_f2, int &nr_bins_f3)
	Get the number of subdivisions for each angular feature interval.
void	setInputNormals (const PointCloudNConstPtr &normals)
	Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
PointCloudNConstPtr	getInputNormals () const
	Get a pointer to the normals of the input XYZ point cloud dataset.
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.
PointCloudInConstPtr	getSearchSurface () const
	Get a pointer to the surface point cloud dataset.
void	setSearchMethod (const KdTreePtr &tree)
	Provide a pointer to the search object.
KdTreePtr	getSearchMethod () const
	Get a pointer to the search method used.
double	getSearchParameter () const
	Get the internal search parameter.
void	setKSearch (int k)
	Set the number of k nearest neighbors to use for the feature estimation.
int	getKSearch () const
	get the number of k nearest neighbors used for the feature estimation.
void	setRadiusSearch (double radius)
	Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation.
double	getRadiusSearch () const
	Get the sphere radius used for determining the neighbors.
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 ()
void	computeEigen (pcl::PointCloud< Eigen::MatrixXf > &output)
	Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
PointCloudConstPtr const	getInputCloud ()
	Get a pointer to the input point cloud dataset.
void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
void	setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud.
IndicesPtr const	getIndices ()
	Get a pointer to the vector of indices used.
const PointInT &	operator[] (size_t pos)
	Override PointCloud operator[] to shorten code.

Detailed Description

template<typename PointInT, typename PointNT>
class pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >

FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals.

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 254 of file fpfh.h.

Member Typedef Documentation

typedef PCLBase<PointInT> pcl::Feature< PointInT, pcl::FPFHSignature33 >::BaseClass [inherited]

Definition at line 110 of file feature.h.

typedef boost::shared_ptr< const FeatureFromNormals<PointInT, PointNT, pcl::FPFHSignature33 > > pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::ConstPtr [inherited]

Reimplemented from pcl::Feature< PointInT, pcl::FPFHSignature33 >.

Definition at line 333 of file feature.h.

typedef pcl::search::Search<PointInT> pcl::Feature< PointInT, pcl::FPFHSignature33 >::KdTree [inherited]

Definition at line 115 of file feature.h.

typedef pcl::search::Search<PointInT>::Ptr pcl::Feature< PointInT, pcl::FPFHSignature33 >::KdTreePtr [inherited]

Definition at line 116 of file feature.h.

typedef pcl::PointCloud<PointInT > pcl::PCLBase< PointInT >::PointCloud [inherited]

Definition at line 74 of file pcl_base.h.

typedef PointCloud::ConstPtr pcl::PCLBase< PointInT >::PointCloudConstPtr [inherited]

Reimplemented in pcl::NormalEstimation< PointInT, PointOutT >, and pcl::NormalEstimation< PointInT, pcl::Normal >.

Definition at line 76 of file pcl_base.h.

typedef pcl::PointCloud<PointNT> pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::PointCloudN [inherited]

Definition at line 328 of file feature.h.

typedef PointCloudN::ConstPtr pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::PointCloudNConstPtr [inherited]

Definition at line 330 of file feature.h.

typedef PointCloudN::Ptr pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::PointCloudNPtr [inherited]

Definition at line 329 of file feature.h.

typedef Feature<PointInT, pcl::FPFHSignature33 >::PointCloudOut pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::PointCloudOut [inherited]

Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >.

Definition at line 91 of file fpfh.h.

typedef PointCloud::Ptr pcl::PCLBase< PointInT >::PointCloudPtr [inherited]

Reimplemented in pcl::OrganizedFastMesh< PointInT >.

Definition at line 75 of file pcl_base.h.

typedef PointIndices::ConstPtr pcl::PCLBase< PointInT >::PointIndicesConstPtr [inherited]

Definition at line 79 of file pcl_base.h.

typedef PointIndices::Ptr pcl::PCLBase< PointInT >::PointIndicesPtr [inherited]

Definition at line 78 of file pcl_base.h.

typedef boost::shared_ptr< FeatureFromNormals<PointInT, PointNT, pcl::FPFHSignature33 > > pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::Ptr [inherited]

Reimplemented from pcl::Feature< PointInT, pcl::FPFHSignature33 >.

Definition at line 332 of file feature.h.

typedef boost::function<int (size_t, double, std::vector<int> &, std::vector<float> &)> pcl::Feature< PointInT, pcl::FPFHSignature33 >::SearchMethod [inherited]

Definition at line 124 of file feature.h.

typedef boost::function<int (const PointCloudIn &cloud, size_t index, double, std::vector<int> &, std::vector<float> &)> pcl::Feature< PointInT, pcl::FPFHSignature33 >::SearchMethodSurface [inherited]

Definition at line 125 of file feature.h.

Member Function Documentation

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::compute ( PointCloudOut & output ) [inherited]

Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters:

[out] output the resultant point cloud model dataset containing the estimated features

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::computeEigen ( pcl::PointCloud< Eigen::MatrixXf > & output ) [inherited]

Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters:

[out] output the resultant point cloud model dataset containing the estimated features

bool pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::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
	)		`[inherited]`

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)

void pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::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
	)		`[inherited]`

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

IndicesPtr const pcl::PCLBase< PointInT >::getIndices ( ) [inline, inherited]

Get a pointer to the vector of indices used.

Definition at line 190 of file pcl_base.h.

PointCloudConstPtr const pcl::PCLBase< PointInT >::getInputCloud ( ) [inline, inherited]

Get a pointer to the input point cloud dataset.

Definition at line 107 of file pcl_base.h.

PointCloudNConstPtr pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::getInputNormals ( ) const [inline, inherited]

Get a pointer to the normals of the input XYZ point cloud dataset.

Definition at line 355 of file feature.h.

int pcl::Feature< PointInT, pcl::FPFHSignature33 >::getKSearch ( ) const [inline, inherited]

get the number of k nearest neighbors used for the feature estimation.

Definition at line 186 of file feature.h.

void pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::getNrSubdivisions	(	int &	nr_bins_f1,
		int &	nr_bins_f2,
		int &	nr_bins_f3
	)		`[inline, inherited]`

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.

double pcl::Feature< PointInT, pcl::FPFHSignature33 >::getRadiusSearch ( ) const [inline, inherited]

Get the sphere radius used for determining the neighbors.

Definition at line 203 of file feature.h.

KdTreePtr pcl::Feature< PointInT, pcl::FPFHSignature33 >::getSearchMethod ( ) const [inline, inherited]

Get a pointer to the search method used.

Definition at line 166 of file feature.h.

double pcl::Feature< PointInT, pcl::FPFHSignature33 >::getSearchParameter ( ) const [inline, inherited]

Get the internal search parameter.

Definition at line 173 of file feature.h.

PointCloudInConstPtr pcl::Feature< PointInT, pcl::FPFHSignature33 >::getSearchSurface ( ) const [inline, inherited]

Get a pointer to the surface point cloud dataset.

Definition at line 153 of file feature.h.

const PointInT & pcl::PCLBase< PointInT >::operator[] ( size_t pos ) [inline, inherited]

Override PointCloud operator[] to shorten code.

Note:: this method can be called instead of (*input_)[(*indices_)[pos]] or input_->points[(*indices_)[pos]]

Parameters:

pos	position in indices_ vector

Definition at line 197 of file pcl_base.h.

void pcl::PCLBase< PointInT >::setIndices ( const IndicesPtr & indices ) [inline, inherited]

Provide a pointer to the vector of indices that represents the input data.

Parameters:

indices a pointer to the vector of indices that represents the input data.

Definition at line 113 of file pcl_base.h.

void pcl::PCLBase< PointInT >::setIndices ( const IndicesConstPtr & indices ) [inline, inherited]

Provide a pointer to the vector of indices that represents the input data.

Parameters:

indices a pointer to the vector of indices that represents the input data.

Definition at line 124 of file pcl_base.h.

void pcl::PCLBase< PointInT >::setIndices ( const PointIndicesConstPtr & indices ) [inline, inherited]

Provide a pointer to the vector of indices that represents the input data.

Parameters:

indices a pointer to the vector of indices that represents the input data.

Definition at line 135 of file pcl_base.h.

void pcl::PCLBase< PointInT >::setIndices	(	size_t	row_start,
		size_t	col_start,
		size_t	nb_rows,
		size_t	nb_cols
	)		`[inline, inherited]`

Set the indices for the points laying within an interest region of the point cloud.

Note:: you shouldn't call this method on unorganized point clouds!

Parameters:

row_start	the offset on rows
col_start	the offset on columns
nb_rows	the number of rows to be considered row_start included
nb_cols	the number of columns to be considered col_start included

Definition at line 151 of file pcl_base.h.

virtual void pcl::PCLBase< PointInT >::setInputCloud ( const PointCloudConstPtr & cloud ) [inline, virtual, inherited]

Provide a pointer to the input dataset.

Parameters:

cloud the const boost shared pointer to a PointCloud message

Definition at line 103 of file pcl_base.h.

void pcl::FeatureFromNormals< PointInT, PointNT, pcl::FPFHSignature33 >::setInputNormals ( const PointCloudNConstPtr & normals ) [inline, inherited]

Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.

In case of search surface is set to be different from the input cloud, normals should correspond to the search surface, not the input cloud!

Parameters:

[in] normals the const boost shared pointer to a PointCloud of normals. By convention, L2 norm of each normal should be 1.

Definition at line 351 of file feature.h.

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::setKSearch ( int k ) [inline, inherited]

Set the number of k nearest neighbors to use for the feature estimation.

Parameters:

[in] k the number of k-nearest neighbors

Definition at line 182 of file feature.h.

void pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::setNrSubdivisions	(	int	nr_bins_f1,
		int	nr_bins_f2,
		int	nr_bins_f3
	)		`[inline, inherited]`

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.

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::setRadiusSearch ( double radius ) [inline, inherited]

Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation.

Parameters:

[in] radius the sphere radius used as the maximum distance to consider a point a neighbor

Definition at line 196 of file feature.h.

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::setSearchMethod ( const KdTreePtr & tree ) [inline, inherited]

Provide a pointer to the search object.

Parameters:

[in] tree a pointer to the spatial search object.

Definition at line 162 of file feature.h.

void pcl::Feature< PointInT, pcl::FPFHSignature33 >::setSearchSurface ( const PointCloudInConstPtr & cloud ) [inline, inherited]

Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset.

This is optional, if this is not set, it will only use the data in the input cloud to estimate the features. This is useful when you only need to compute the features for a downsampled cloud.

Parameters:

[in] cloud a pointer to a PointCloud message

Definition at line 144 of file feature.h.

void pcl::FPFHEstimation< PointInT, PointNT, pcl::FPFHSignature33 >::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
	)		`[inherited]`

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

The documentation for this class was generated from the following files:

/usr/src/RPM/BUILD/PCL-1.6.0-Source/features/include/pcl/features/fpfh.h
/usr/src/RPM/BUILD/PCL-1.6.0-Source/features/include/pcl/features/impl/fpfh.hpp

Public Types

Public Member Functions

Detailed Description

template<typename PointInT, typename PointNT> class pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >

Member Typedef Documentation

Member Function Documentation

template<typename PointInT, typename PointNT>
class pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >