Point Cloud Library (PCL)  1.14.1-dev
List of all members | Public Types | Public Member Functions | Protected Member Functions | Protected Attributes
pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT > Class Template Reference

PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More...

#include <pcl/features/principal_curvatures.h>

+ Inheritance diagram for pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >:
+ Collaboration diagram for pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >:

Public Types

using Ptr = shared_ptr< PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT > >
 
using ConstPtr = shared_ptr< const PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT > >
 
using PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut
 
using PointCloudIn = pcl::PointCloud< PointInT >
 
- Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures >
using PointCloudN = pcl::PointCloud< PointNT >
 
using PointCloudNPtr = typename PointCloudN::Ptr
 
using PointCloudNConstPtr = typename PointCloudN::ConstPtr
 
using Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures > >
 
using ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures > >
 
- 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 = pcl::PointCloud< PointInT >
 
using PointCloudPtr = typename PointCloud::Ptr
 
using PointCloudConstPtr = typename PointCloud::ConstPtr
 
using PointIndicesPtr = PointIndices::Ptr
 
using PointIndicesConstPtr = PointIndices::ConstPtr
 

Public Member Functions

 PrincipalCurvaturesEstimation (unsigned int nr_threads=1, int chunk_size=256)
 Initialize the scheduler and set the number of threads to use. More...
 
void computePointPrincipalCurvatures (const pcl::PointCloud< PointNT > &normals, int p_idx, const pcl::Indices &indices, float &pcx, float &pcy, float &pcz, float &pc1, float &pc2)
 Perform Principal Components Analysis (PCA) on the point normals of a surface patch in the tangent plane of the given point normal, and return the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues. More...
 
void setNumberOfThreads (unsigned int nr_threads)
 Initialize the scheduler and set the number of threads to use. More...
 
- Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures >
 FeatureFromNormals ()
 Empty constructor. 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, PointOutT >
 Feature ()
 Empty constructor. 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...
 
PointCloudConstPtr const 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...
 
IndicesConstPtr const 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 computeFeature (PointCloudOut &output) override
 Estimate the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More...
 
- Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures >
virtual bool initCompute ()
 This method should get called before starting the actual computation. More...
 
- Protected Member Functions inherited from pcl::Feature< PointInT, PointOutT >
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

unsigned int threads_
 The number of threads the scheduler should use. More...
 
int chunk_size_
 Chunk size for (dynamic) scheduling. More...
 
- Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PrincipalCurvatures >
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, PointOutT >
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::PrincipalCurvatures>
class pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >

PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals.

The output contains the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues. Parallel execution is supported through OpenMP.

The recommended PointOutT is pcl::PrincipalCurvatures.

Author
Radu B. Rusu, Jared Glover, Alex Navarro

Definition at line 58 of file principal_curvatures.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
using pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const PrincipalCurvaturesEstimation<PointInT, PointNT, PointOutT> >

Definition at line 62 of file principal_curvatures.h.

◆ PointCloudIn

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
using pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::PointCloudIn = pcl::PointCloud<PointInT>

Definition at line 73 of file principal_curvatures.h.

◆ PointCloudOut

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
using pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 72 of file principal_curvatures.h.

◆ Ptr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
using pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<PrincipalCurvaturesEstimation<PointInT, PointNT, PointOutT> >

Definition at line 61 of file principal_curvatures.h.

Constructor & Destructor Documentation

◆ PrincipalCurvaturesEstimation()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::PrincipalCurvaturesEstimation ( unsigned int  nr_threads = 1,
int  chunk_size = 256 
)
inline

Initialize the scheduler and set the number of threads to use.

Parameters
nr_threadsthe number of hardware threads to use (0 sets the value to automatic)
chunk_sizePCL will use dynamic scheduling with this chunk size. Setting it too low will lead to more parallelization overhead. Setting it too high will lead to a worse balancing between the threads.

Definition at line 81 of file principal_curvatures.h.

References pcl::Feature< PointInT, PointOutT >::feature_name_, and pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::setNumberOfThreads().

Member Function Documentation

◆ computeFeature()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computeFeature ( PointCloudOut output)
overrideprotectedvirtual

Estimate the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters
[out]outputthe resultant point cloud model dataset that contains the principal curvature estimates

Implements pcl::Feature< PointInT, PointOutT >.

Definition at line 129 of file principal_curvatures.hpp.

References pcl::PointCloud< PointT >::is_dense, and pcl::isFinite().

◆ computePointPrincipalCurvatures()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computePointPrincipalCurvatures ( const pcl::PointCloud< PointNT > &  normals,
int  p_idx,
const pcl::Indices indices,
float &  pcx,
float &  pcy,
float &  pcz,
float &  pc1,
float &  pc2 
)

Perform Principal Components Analysis (PCA) on the point normals of a surface patch in the tangent plane of the given point normal, and return the principal curvature (eigenvector of the max eigenvalue), along with both the max (pc1) and min (pc2) eigenvalues.

Parameters
[in]normalsthe point cloud normals
[in]p_idxthe query point at which the least-squares plane was estimated
[in]indicesthe point cloud indices that need to be used
[out]pcxthe principal curvature X direction
[out]pcythe principal curvature Y direction
[out]pczthe principal curvature Z direction
[out]pc1the max eigenvalue of curvature
[out]pc2the min eigenvalue of curvature

Definition at line 66 of file principal_curvatures.hpp.

References pcl::computeCorrespondingEigenVector(), and pcl::eigen33().

◆ setNumberOfThreads()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::setNumberOfThreads ( unsigned int  nr_threads)

Initialize the scheduler and set the number of threads to use.

The default behavior is single threaded exectution

Parameters
nr_threadsthe number of hardware threads to use (0 sets the value to automatic)

Definition at line 49 of file principal_curvatures.hpp.

Referenced by pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::PrincipalCurvaturesEstimation().

Member Data Documentation

◆ chunk_size_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
int pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::chunk_size_
protected

Chunk size for (dynamic) scheduling.

Definition at line 118 of file principal_curvatures.h.

◆ threads_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::PrincipalCurvatures>
unsigned int pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::threads_
protected

The number of threads the scheduler should use.

Definition at line 115 of file principal_curvatures.h.


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