GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals. More...

#include <pcl/features/grsd.h>

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

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

Public Types
using	PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

using	PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn

using	PointCloudInPtr = typename Feature<PointInT, PointOutT>::PointCloudInPtr

Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >
using	PointCloudN = pcl::PointCloud<PointNT>

using	PointCloudNPtr = typename PointCloudN::Ptr

using	PointCloudNConstPtr = typename PointCloudN::ConstPtr

using	Ptr = shared_ptr< FeatureFromNormals<PointInT, PointNT, PointOutT> >

using	ConstPtr = shared_ptr< const FeatureFromNormals<PointInT, PointNT, PointOutT> >

Public Types inherited from pcl::Feature< PointInT, PointOutT >
using	BaseClass = PCLBase<PointInT>

using	Ptr = shared_ptr< Feature<PointInT, PointOutT> >

using	ConstPtr = shared_ptr< const Feature<PointInT, PointOutT> >

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<PointOutT>

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

using	PointCloudPtr

using	PointCloudConstPtr

using	PointIndicesPtr

using	PointIndicesConstPtr

Public Member Functions
	GRSDEstimation ()
	Constructor.

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.

Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >
	FeatureFromNormals ()
	Empty constructor.

virtual	~FeatureFromNormals ()
	Empty destructor.

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, PointOutT >
	Feature ()
	Empty constructor.

virtual	~Feature ()
	Empty destructor.

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.

Static Public Member Functions
static int	getSimpleType (float min_radius, float max_radius, double min_radius_plane=0.100, double max_radius_noise=0.015, double min_radius_cylinder=0.175, double max_min_radius_diff=0.050)
	Get the type of the local surface based on the min and max radius computed.

Protected Member Functions
void	computeFeature (PointCloudOut &output) override
	Estimate the Global Radius-based Surface Descriptor (GRSD) for 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, PointOutT >
virtual bool	initCompute ()
	This method should get called before starting the actual computation.

Protected Member Functions inherited from pcl::Feature< PointInT, PointOutT >
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.

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.

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.

Additional Inherited Members
Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >
PointCloudNConstPtr	normals_
	A pointer to the input dataset that contains the point normals of the XYZ dataset.

Protected Attributes inherited from pcl::Feature< PointInT, PointOutT >
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>
class pcl::GRSDEstimation< PointInT, PointNT, PointOutT >

GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals.

Note: If you use this code in any academic work, please cite (first for the ray-casting and second for the additive version):

Z.C. Marton, D. Pangercic, N. Blodow, Michael Beetz. Combined 2D-3D Categorization and Classification for Multimodal Perception Systems. In The International Journal of Robotics Research, Sage Publications pages 1378–1402, Volume 30, Number 11, September 2011.
A. Kanezaki, Z.C. Marton, D. Pangercic, T. Harada, Y. Kuniyoshi, M. Beetz. Voxelized Shape and Color Histograms for RGB-D In the Workshop on Active Semantic Perception and Object Search in the Real World, in conjunction with the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) San Francisco, California, September 25-30, 2011.

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: Zoltan Csaba Marton

Definition at line 71 of file grsd.h.

Member Typedef Documentation

◆ PointCloudIn

template<typename PointInT , typename PointNT , typename PointOutT >

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

Definition at line 85 of file grsd.h.

◆ PointCloudInPtr

template<typename PointInT , typename PointNT , typename PointOutT >

using pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::PointCloudInPtr = typename Feature<PointInT, PointOutT>::PointCloudInPtr

Definition at line 86 of file grsd.h.

◆ PointCloudOut

template<typename PointInT , typename PointNT , typename PointOutT >

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

Definition at line 84 of file grsd.h.

Constructor & Destructor Documentation

◆ GRSDEstimation()

template<typename PointInT , typename PointNT , typename PointOutT >

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

inline

Constructor.

Definition at line 89 of file grsd.h.

References pcl::Feature< PointInT, PointOutT >::feature_name_, and pcl::getAllNeighborCellIndices().

Member Function Documentation

◆ computeFeature()

template<typename PointInT , typename PointNT , typename PointOutT >

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

overrideprotectedvirtual

Estimate the Global Radius-based Surface Descriptor (GRSD) for a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters

output the resultant point cloud that contains the GRSD feature

Implements pcl::Feature< PointInT, PointOutT >.

Definition at line 65 of file grsd.hpp.

References pcl::Feature< PointInT, PointOutT >::compute(), pcl::Filter< PointT >::filter(), pcl::VoxelGrid< PointT >::getNeighborCentroidIndices(), pcl::PCLBase< PointT >::setInputCloud(), pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >::setInputNormals(), pcl::VoxelGrid< PointT >::setLeafSize(), pcl::Feature< PointInT, PointOutT >::setRadiusSearch(), pcl::VoxelGrid< PointT >::setSaveLeafLayout(), and pcl::Feature< PointInT, PointOutT >::setSearchSurface().

◆ getRadiusSearch()

template<typename PointInT , typename PointNT , typename PointOutT >

double pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::getRadiusSearch ( ) const

inline

Get the sphere radius used for determining the neighbors.

Returns: the sphere radius used as the maximum distance to consider a point a neighbor

Definition at line 106 of file grsd.h.

References pcl::Feature< PointInT, PointOutT >::search_radius_.

◆ getSimpleType()

template<typename PointInT , typename PointNT , typename PointOutT >

int pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::getSimpleType	(	float	min_radius,
		float	max_radius,
		double	min_radius_plane = 0.100,
		double	max_radius_noise = 0.015,
		double	min_radius_cylinder = 0.175,
		double	max_min_radius_diff = 0.050 )

inlinestatic

Get the type of the local surface based on the min and max radius computed.

Returns: the integer that represents the type of the local surface with values as Plane (1), Cylinder (2), Noise or corner (0), Sphere (3) and Edge (4)

Definition at line 46 of file grsd.hpp.

◆ setRadiusSearch()

template<typename PointInT , typename PointNT , typename PointOutT >

void pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::setRadiusSearch ( double radius )

inline

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

Same value will be used for the internal voxel grid leaf size.

Parameters

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

Definition at line 100 of file grsd.h.

References pcl::Feature< PointInT, PointOutT >::search_radius_.

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

pcl/features/grsd.h
pcl/features/impl/grsd.hpp

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ PointCloudIn

◆ PointCloudInPtr

◆ PointCloudOut

Constructor & Destructor Documentation

◆ GRSDEstimation()

Member Function Documentation

◆ computeFeature()

◆ getRadiusSearch()

◆ getSimpleType()

◆ setRadiusSearch()