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

#include <pcl/features/pfh.h>

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

Collaboration diagram for pcl::PFHEstimation< PointInT, PointNT, PointOutT >:

Public Types
using	Ptr = shared_ptr<PFHEstimation<PointInT, PointNT, PointOutT> >
using	ConstPtr = shared_ptr<const PFHEstimation<PointInT, PointNT, PointOutT> >
using	PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut
using	PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn
Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 >
using	PointCloudN
using	PointCloudNPtr
using	PointCloudNConstPtr
using	Ptr
using	ConstPtr
Public Types inherited from pcl::Feature< PointInT, pcl::PFHSignature125 >
using	BaseClass
using	Ptr
using	ConstPtr
using	KdTree
using	KdTreePtr
using	PointCloudIn
using	PointCloudInPtr
using	PointCloudInConstPtr
using	PointCloudOut
using	SearchMethod
using	SearchMethodSurface
Public Types inherited from pcl::PCLBase< PointInT >
using	PointCloud
using	PointCloudPtr
using	PointCloudConstPtr
using	PointIndicesPtr
using	PointIndicesConstPtr

Public Member Functions
	PFHEstimation ()
	Empty constructor.
void	setMaximumCacheSize (unsigned int cache_size)
	Set the maximum internal cache size.
unsigned int	getMaximumCacheSize ()
	Get the maximum internal cache size.
void	setUseInternalCache (bool use_cache)
	Set whether to use an internal cache mechanism for removing redundant calculations or not.
bool	getUseInternalCache ()
	Get whether the internal cache is used or not for computing the PFH features.
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	computePointPFHSignature (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, int nr_split, Eigen::VectorXf &pfh_histogram)
	Estimate the PFH (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.
Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 >
	FeatureFromNormals ()
	Empty constructor.
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.
Public Member Functions inherited from pcl::Feature< PointInT, pcl::PFHSignature125 >
	Feature ()
	Empty constructor.
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 ()
Public Member Functions inherited from pcl::PCLBase< PointInT >
	PCLBase ()
	Empty constructor.
	PCLBase (const PCLBase &base)
	Copy constructor.
virtual	~PCLBase ()=default
	Destructor.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.
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.
IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used.
IndicesConstPtr const	getIndices () const
	Get a pointer to the vector of indices used.
const PointInT &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code.

Protected Member Functions
void	computeFeature (PointCloudOut &output) override
	Estimate the Point Feature Histograms (PFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 >
virtual bool	initCompute ()
	This method should get called before starting the actual computation.
Protected Member Functions inherited from pcl::Feature< PointInT, pcl::PFHSignature125 >
const std::string &	getClassName () const
	Get a string representation of the name of this class.
virtual bool	deinitCompute ()
	This method should get called after ending the actual computation.
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.
Protected Member Functions inherited from pcl::PCLBase< PointInT >
bool	initCompute ()
	This method should get called before starting the actual computation.
bool	deinitCompute ()
	This method should get called after finishing the actual computation.

Protected Attributes
int	nr_subdiv_ {5}
	The number of subdivisions for each angular feature interval.
Eigen::VectorXf	pfh_histogram_
	Placeholder for a point's PFH signature.
Eigen::Vector4f	pfh_tuple_
	Placeholder for a PFH 4-tuple.
int	f_index_ [3]
	Placeholder for a histogram index.
float	d_pi_
	Float constant = 1.0 / (2.0 * M_PI)
std::map< std::pair< int, int >, Eigen::Vector4f, std::less<>, Eigen::aligned_allocator< std::pair< const std::pair< int, int >, Eigen::Vector4f > > >	feature_map_
	Internal hashmap, used to optimize efficiency of redundant computations.
std::queue< std::pair< int, int > >	key_list_
	Queue of pairs saved, used to constrain memory usage.
unsigned int	max_cache_size_
	Maximum size of internal cache memory.
bool	use_cache_ {false}
	Set to true to use the internal cache for removing redundant computations.
Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 >
PointCloudNConstPtr	normals_
	A pointer to the input dataset that contains the point normals of the XYZ dataset.
Protected Attributes inherited from pcl::Feature< PointInT, pcl::PFHSignature125 >
std::string	feature_name_
	The feature name.
SearchMethodSurface	search_method_surface_
	The search method template for points.
PointCloudInConstPtr	surface_
	An input point cloud describing the surface that is to be used for nearest neighbors estimation.
KdTreePtr	tree_
	A pointer to the spatial search object.
double	search_parameter_
	The actual search parameter (from either search_radius_ or k_).
double	search_radius_
	The nearest neighbors search radius for each point.
int	k_
	The number of K nearest neighbors to use for each point.
bool	fake_surface_
	If no surface is given, we use the input PointCloud as the surface.
Protected Attributes inherited from pcl::PCLBase< PointInT >
PointCloudConstPtr	input_
	The input point cloud dataset.
IndicesPtr	indices_
	A pointer to the vector of point indices to use.
bool	use_indices_
	Set to true if point indices are used.
bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.

Detailed Description

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>
class pcl::PFHEstimation< PointInT, PointNT, PointOutT >

PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals.

A commonly used type for PointOutT is pcl::PFHSignature125.

Note: If you use this code in any academic work, please cite:

R.B. Rusu, N. Blodow, Z.C. Marton, M. Beetz. Aligning Point Cloud Views using Persistent Feature Histograms. In Proceedings of the 21st IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, September 22-26 2008.
R.B. Rusu, Z.C. Marton, N. Blodow, M. Beetz. Learning Informative Point Classes for the Acquisition of Object Model Maps. In Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision (ICARCV), Hanoi, Vietnam, December 17-20 2008.

Attention

The convention for PFH features is:

if a query point's nearest neighbors cannot be estimated, the PFH feature will be set to NaN (not a number)
it is impossible to estimate a PFH 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 PFH 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 81 of file pfh.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const PFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 85 of file pfh.h.

◆ PointCloudIn

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn

Definition at line 96 of file pfh.h.

◆ PointCloudOut

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 95 of file pfh.h.

◆ Ptr

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<PFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 84 of file pfh.h.

Constructor & Destructor Documentation

◆ PFHEstimation()

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

pcl::PFHEstimation< PointInT, PointNT, PointOutT >::PFHEstimation ( )

inline

Empty constructor.

Sets use_cache_ to false, nr_subdiv_ to 5, and the internal maximum cache size to 1GB.

Definition at line 101 of file pfh.h.

References d_pi_, pcl::Feature< PointInT, pcl::PFHSignature125 >::feature_name_, key_list_, M_PI, and max_cache_size_.

Member Function Documentation

◆ computeFeature()

template<typename PointInT, typename PointNT, typename PointOutT>

void pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computeFeature ( PointCloudOut & output )

overrideprotected

Estimate the Point Feature Histograms (PFH) 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 PFH feature estimates

Definition at line 167 of file pfh.hpp.

References computePointPFHSignature(), feature_map_, pcl::PCLBase< PointInT >::indices_, pcl::PCLBase< PointInT >::input_, pcl::isFinite(), pcl::Feature< PointInT, pcl::PFHSignature125 >::k_, key_list_, pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 >::normals_, nr_subdiv_, pfh_histogram_, pcl::Feature< PointInT, pcl::PFHSignature125 >::search_parameter_, pcl::Feature< PointInT, pcl::PFHSignature125 >::searchForNeighbors(), and pcl::Feature< PointInT, pcl::PFHSignature125 >::surface_.

◆ computePairFeatures()

template<typename PointInT, typename PointNT, typename PointOutT>

bool pcl::PFHEstimation< 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)

Note: For efficiency reasons, we assume that the point data passed to the method is finite.

Definition at line 49 of file pfh.hpp.

References pcl::computePairFeatures().

Referenced by computePointPFHSignature().

◆ computePointPFHSignature()

template<typename PointInT, typename PointNT, typename PointOutT>

void pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature	(	const pcl::PointCloud< PointInT > &	cloud,
		const pcl::PointCloud< PointNT > &	normals,
		const pcl::Indices &	indices,
		int	nr_split,
		Eigen::VectorXf &	pfh_histogram )

Estimate the PFH (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]	indices	the k-neighborhood point indices in the dataset
[in]	nr_split	the number of subdivisions for each angular feature interval
[out]	pfh_histogram	the resultant (combinatorial) PFH histogram representing the feature at the query point

Definition at line 61 of file pfh.hpp.

References computePairFeatures(), d_pi_, f_index_, feature_map_, pcl::isFinite(), key_list_, M_PI, max_cache_size_, pfh_tuple_, and use_cache_.

Referenced by computeFeature().

◆ getMaximumCacheSize()

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

unsigned int pcl::PFHEstimation< PointInT, PointNT, PointOutT >::getMaximumCacheSize ( )

inline

Get the maximum internal cache size.

Definition at line 122 of file pfh.h.

References max_cache_size_.

◆ getUseInternalCache()

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

bool pcl::PFHEstimation< PointInT, PointNT, PointOutT >::getUseInternalCache ( )

inline

Get whether the internal cache is used or not for computing the PFH features.

Definition at line 146 of file pfh.h.

References use_cache_.

◆ setMaximumCacheSize()

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

void pcl::PFHEstimation< PointInT, PointNT, PointOutT >::setMaximumCacheSize ( unsigned int cache_size )

inline

Set the maximum internal cache size.

Defaults to 2GB worth of entries.

Parameters

[in] cache_size maximum cache size

Definition at line 115 of file pfh.h.

References max_cache_size_.

◆ setUseInternalCache()

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

void pcl::PFHEstimation< PointInT, PointNT, PointOutT >::setUseInternalCache ( bool use_cache )

inline

Set whether to use an internal cache mechanism for removing redundant calculations or not.

Note: Depending on how the point cloud is ordered and how the nearest neighbors are estimated, using a cache could have a positive or a negative influence. Please test with and without a cache on your data, and choose whatever works best!

See setMaximumCacheSize for setting the maximum cache size

Parameters

[in] use_cache set to true to use the internal cache, false otherwise

Definition at line 139 of file pfh.h.

References use_cache_.

Member Data Documentation

◆ d_pi_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

float pcl::PFHEstimation< PointInT, PointNT, PointOutT >::d_pi_

protected

Float constant = 1.0 / (2.0 * M_PI)

Definition at line 203 of file pfh.h.

Referenced by computePointPFHSignature(), and PFHEstimation().

◆ f_index_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

int pcl::PFHEstimation< PointInT, PointNT, PointOutT >::f_index_[3]

protected

Placeholder for a histogram index.

Definition at line 200 of file pfh.h.

Referenced by computePointPFHSignature().

◆ feature_map_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

std::map<std::pair<int, int>, Eigen::Vector4f, std::less<>, Eigen::aligned_allocator<std::pair<const std::pair<int, int>, Eigen::Vector4f> > > pcl::PFHEstimation< PointInT, PointNT, PointOutT >::feature_map_

protected

Internal hashmap, used to optimize efficiency of redundant computations.

Definition at line 206 of file pfh.h.

Referenced by computeFeature(), and computePointPFHSignature().

◆ key_list_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

std::queue<std::pair<int, int> > pcl::PFHEstimation< PointInT, PointNT, PointOutT >::key_list_

protected

Queue of pairs saved, used to constrain memory usage.

Definition at line 209 of file pfh.h.

Referenced by computeFeature(), computePointPFHSignature(), and PFHEstimation().

◆ max_cache_size_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

unsigned int pcl::PFHEstimation< PointInT, PointNT, PointOutT >::max_cache_size_

protected

Maximum size of internal cache memory.

Definition at line 212 of file pfh.h.

Referenced by computePointPFHSignature(), getMaximumCacheSize(), PFHEstimation(), and setMaximumCacheSize().

◆ nr_subdiv_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

int pcl::PFHEstimation< PointInT, PointNT, PointOutT >::nr_subdiv_ {5}

protected

The number of subdivisions for each angular feature interval.

Definition at line 191 of file pfh.h.

Referenced by computeFeature().

◆ pfh_histogram_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

Eigen::VectorXf pcl::PFHEstimation< PointInT, PointNT, PointOutT >::pfh_histogram_

protected

Placeholder for a point's PFH signature.

Definition at line 194 of file pfh.h.

Referenced by computeFeature().

◆ pfh_tuple_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

Eigen::Vector4f pcl::PFHEstimation< PointInT, PointNT, PointOutT >::pfh_tuple_

protected

Placeholder for a PFH 4-tuple.

Definition at line 197 of file pfh.h.

Referenced by computePointPFHSignature().

◆ use_cache_

template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>

bool pcl::PFHEstimation< PointInT, PointNT, PointOutT >::use_cache_ {false}

protected

Set to true to use the internal cache for removing redundant computations.

Definition at line 215 of file pfh.h.

Referenced by computePointPFHSignature(), getUseInternalCache(), and setUseInternalCache().

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

pcl/features/pfh.h
pcl/features/impl/pfh.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ ConstPtr

◆ PointCloudIn

◆ PointCloudOut

◆ Ptr

Constructor & Destructor Documentation

◆ PFHEstimation()

Member Function Documentation

◆ computeFeature()

◆ computePairFeatures()

◆ computePointPFHSignature()

◆ getMaximumCacheSize()

◆ getUseInternalCache()

◆ setMaximumCacheSize()

◆ setUseInternalCache()

Member Data Documentation

◆ d_pi_

◆ f_index_

◆ feature_map_

◆ key_list_

◆ max_cache_size_

◆ nr_subdiv_

◆ pfh_histogram_

◆ pfh_tuple_

◆ use_cache_