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

#include <fpfh.h>

Inheritance diagram for pcl::FPFHEstimation< PointInT, PointNT, PointOutT >:

[legend]

List of all members.

Public Types
typedef Feature< PointInT, PointOutT >::PointCloudOut	PointCloudOut
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.
	FPFHEstimation ()
	Empty constructor.
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	setNrSubdivisions (int nr_bins_f1, int nr_bins_f2, int nr_bins_f3)
	Set the number of subdivisions for each angular feature interval.
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.
Protected Member Functions
void	computeFeature (PointCloudOut &output)
	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 ()
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.
Protected Attributes
float	d_pi_
	Float constant = 1.0 / (2.0 * M_PI)
Eigen::VectorXf	fpfh_histogram_
	Placeholder for a point's FPFH signature.
Eigen::MatrixXf	hist_f1_
	Placeholder for the f1 histogram.
Eigen::MatrixXf	hist_f2_
	Placeholder for the f2 histogram.
Eigen::MatrixXf	hist_f3_
	Placeholder for the f3 histogram.
int	nr_bins_f1_
	The number of subdivisions for each angular feature interval.
int	nr_bins_f2_
int	nr_bins_f3_
Private Member Functions
void	computeFeatureEigen (pcl::PointCloud< Eigen::MatrixXf > &)
	Make the computeFeature (&Eigen::MatrixXf); inaccessible from outside the class.

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 79 of file fpfh.h.

Member Typedef Documentation

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>

typedef Feature<PointInT, PointOutT>::PointCloudOut pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut

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

Reimplemented in pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 91 of file fpfh.h.

Constructor & Destructor Documentation

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>

pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::FPFHEstimation ( ) [inline]

Empty constructor.

Definition at line 94 of file fpfh.h.

Member Function Documentation

template<typename PointInT , typename PointNT , typename PointOutT >

void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature ( PointCloudOut & output ) [protected, virtual]

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

Implements pcl::Feature< PointInT, PointOutT >.

Reimplemented in pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 233 of file fpfh.hpp.

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>

void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeatureEigen ( pcl::PointCloud< Eigen::MatrixXf > & ) [inline, private, virtual]

Make the computeFeature (&Eigen::MatrixXf); inaccessible from outside the class.

Parameters:

[out] output the output point cloud

Implements pcl::Feature< PointInT, PointOutT >.

Reimplemented in pcl::FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >, pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 222 of file fpfh.h.

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 48 of file fpfh.hpp.

template<typename PointInT, typename PointNT, typename PointOutT >

void pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::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.

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 60 of file fpfh.hpp.

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]	spfh_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 173 of file fpfh.hpp.

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.

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.

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 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.

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 105 of file fpfh.hpp.

Member Data Documentation

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.

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.

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.

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.

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.

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.

Reimplemented in pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 200 of file fpfh.h.

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>

int pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f2_ [protected]

Reimplemented in pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 200 of file fpfh.h.

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>

int pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::nr_bins_f3_ [protected]

Reimplemented in pcl::FPFHEstimationOMP< PointInT, PointNT, PointOutT >, and pcl::FPFHEstimationOMP< PointType, pcl::Normal, pcl::FPFHSignature33 >.

Definition at line 200 of file fpfh.h.

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

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Detailed Description

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33> class pcl::FPFHEstimation< PointInT, PointNT, PointOutT >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename PointInT, typename PointNT, typename PointOutT = pcl::FPFHSignature33>
class pcl::FPFHEstimation< PointInT, PointNT, PointOutT >