point_cloud_library / 1.12.1 / classpcl_1_1_o_u_r_c_v_f_h_estimation.html /

OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset given XYZ data and normals, as presented in: More...

#include <pcl/features/our_cvfh.h>

Public Types

using Ptr = shared_ptr< OURCVFHEstimation< PointInT, PointNT, PointOutT > >
using ConstPtr = shared_ptr< const OURCVFHEstimation< PointInT, PointNT, PointOutT > >
using PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut
using KdTreePtr = typename pcl::search::Search< PointNormal >::Ptr
using PointInTPtr = typename pcl::PointCloud< PointInT >::Ptr
- Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
using PointCloudN = pcl::PointCloud< PointNT >
using PointCloudNPtr = typename PointCloudN::Ptr
using PointCloudNConstPtr = typename PointCloudN::ConstPtr
using Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > >
using ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > >
- Public Types inherited from pcl::Feature< PointInT, pcl::VFHSignature308 >
using BaseClass = PCLBase< PointInT >
using Ptr = shared_ptr< Feature< PointInT, pcl::VFHSignature308 > >
using ConstPtr = shared_ptr< const Feature< PointInT, pcl::VFHSignature308 > >
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< pcl::VFHSignature308 >
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

OURCVFHEstimation ()
Empty constructor. More...
Eigen::Matrix4f createTransFromAxes (Eigen::Vector3f &evx, Eigen::Vector3f &evy, Eigen::Vector3f &evz, Eigen::Affine3f &transformPC, Eigen::Matrix4f &center_mat)
Creates an affine transformation from the RF axes. More...
void computeRFAndShapeDistribution (PointInTPtr &processed, PointCloudOut &output, std::vector< pcl::PointIndices > &cluster_indices)
Computes SGURF and the shape distribution based on the selected SGURF. More...
bool sgurf (Eigen::Vector3f &centroid, Eigen::Vector3f &normal_centroid, PointInTPtr &processed, std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &transformations, PointInTPtr &grid, pcl::PointIndices &indices)
Computes SGURF. More...
void filterNormalsWithHighCurvature (const pcl::PointCloud< PointNT > &cloud, pcl::Indices &indices_to_use, pcl::Indices &indices_out, pcl::Indices &indices_in, float threshold)
Removes normals with high curvature caused by real edges or noisy data. More...
void setViewPoint (float vpx, float vpy, float vpz)
Set the viewpoint. More...
void setRadiusNormals (float radius_normals)
Set the radius used to compute normals. More...
void getViewPoint (float &vpx, float &vpy, float &vpz)
Get the viewpoint. More...
void getCentroidClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &centroids)
Get the centroids used to compute different CVFH descriptors. More...
void getCentroidNormalClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &centroids)
Get the normal centroids used to compute different CVFH descriptors. More...
void setClusterTolerance (float d)
Sets max. More...
void setEPSAngleThreshold (float d)
Sets max. More...
void setCurvatureThreshold (float d)
Sets curvature threshold for removing normals. More...
void setMinPoints (std::size_t min)
Set minimum amount of points for a cluster to be considered. More...
void setNormalizeBins (bool normalize)
Sets whether the signatures should be normalized or not. More...
void getClusterIndices (std::vector< pcl::PointIndices > &indices)
Gets the indices of the original point cloud used to compute the signatures. More...
void getClusterAxes (std::vector< short > &cluster_axes)
Gets the number of non-disambiguable axes that correspond to each centroid. More...
void setRefineClusters (float rc)
Sets the refinement factor for the clusters. More...
void getTransforms (std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &trans)
Returns the transformations aligning the point cloud to the corresponding SGURF. More...
void getValidTransformsVec (std::vector< bool > &valid)
Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a valid SGURF. More...
void setAxisRatio (float f)
Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible. More...
void setMinAxisValue (float f)
Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition is difficult. More...
void compute (PointCloudOut &output)
Overloaded computed method from pcl::Feature. More...
- Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
FeatureFromNormals ()
Empty constructor. More...
virtual ~FeatureFromNormals ()
Empty destructor. 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, pcl::VFHSignature308 >
Feature ()
Empty constructor. More...
virtual ~Feature ()
Empty destructor. 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...
const PointCloudConstPtr 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...
const IndicesConstPtr 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 Attributes

std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > centroids_dominant_orientations_
Centroids that were used to compute different OUR-CVFH descriptors. More...
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > dominant_normals_
Normal centroids that were used to compute different OUR-CVFH descriptors. More...
std::vector< pcl::PointIndices > clusters_
Indices to the points representing the stable clusters. More...
std::vector< short > cluster_axes_
Mapping from clusters to OUR-CVFH descriptors. More...
- Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
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, pcl::VFHSignature308 >
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...

Additional Inherited Members

- Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 >
virtual bool initCompute ()
This method should get called before starting the actual computation. More...
- Protected Member Functions inherited from pcl::Feature< PointInT, pcl::VFHSignature308 >
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...

Detailed Description

template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308>
class pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >

OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset given XYZ data and normals, as presented in:

  • OUR-CVFH – Oriented, Unique and Repeatable Clustered Viewpoint Feature Histogram for Object Recognition and 6DOF Pose Estimation A. Aldoma, F. Tombari, R.B. Rusu and M. Vincze DAGM-OAGM 2012 Graz, Austria The suggested PointOutT is pcl::VFHSignature308.
Author
Aitor Aldoma

Definition at line 59 of file our_cvfh.h.

Member Typedef Documentation

ConstPtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const OURCVFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 63 of file our_cvfh.h.

KdTreePtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::KdTreePtr = typename pcl::search::Search<PointNormal>::Ptr

Definition at line 73 of file our_cvfh.h.

PointCloudOut

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 72 of file our_cvfh.h.

PointInTPtr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointInTPtr = typename pcl::PointCloud<PointInT>::Ptr

Definition at line 74 of file our_cvfh.h.

Ptr

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<OURCVFHEstimation<PointInT, PointNT, PointOutT> >

Definition at line 62 of file our_cvfh.h.

Constructor & Destructor Documentation

OURCVFHEstimation()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::OURCVFHEstimation ( )
inline

Member Function Documentation

compute()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::compute ( PointCloudOut & output )

Overloaded computed method from pcl::Feature.

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

Definition at line 53 of file our_cvfh.hpp.

computeRFAndShapeDistribution()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution ( PointInTPtr & processed,
PointCloudOut & output,
std::vector< pcl::PointIndices > & cluster_indices
)

Computes SGURF and the shape distribution based on the selected SGURF.

Parameters
[in] processed the input cloud
[out] output the resulting signature
[in] cluster_indices the indices of the stable cluster

Definition at line 381 of file our_cvfh.hpp.

References pcl::getMaxDistance(), and pcl::transformPointCloud().

createTransFromAxes()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
Eigen::Matrix4f pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::createTransFromAxes ( Eigen::Vector3f & evx,
Eigen::Vector3f & evy,
Eigen::Vector3f & evz,
Eigen::Affine3f & transformPC,
Eigen::Matrix4f & center_mat
)
inline

Creates an affine transformation from the RF axes.

Parameters
[in] evx the x-axis
[in] evy the y-axis
[in] evz the z-axis
[out] transformPC the resulting transformation
[in] center_mat 4x4 matrix concatenated to the resulting transformation

Definition at line 97 of file our_cvfh.h.

filterNormalsWithHighCurvature()

template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature ( const pcl::PointCloud< PointNT > & cloud,
pcl::Indices & indices_to_use,
pcl::Indices & indices_out,
pcl::Indices & indices_in,
float threshold
)

Removes normals with high curvature caused by real edges or noisy data.

Parameters
[in] cloud pointcloud to be filtered
[in] indices_to_use
[out] indices_out the indices of the points with higher curvature than threshold
[out] indices_in the indices of the remaining points after filtering
[in] threshold threshold value for curvature

Definition at line 168 of file our_cvfh.hpp.

References pcl::PointCloud< PointT >::size().

getCentroidClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidClusters ( std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > & centroids )
inline

Get the centroids used to compute different CVFH descriptors.

Parameters
[out] centroids vector to hold the centroids

Definition at line 191 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_.

getCentroidNormalClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidNormalClusters ( std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > & centroids )
inline

Get the normal centroids used to compute different CVFH descriptors.

Parameters
[out] centroids vector to hold the normal centroids

Definition at line 201 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_.

getClusterAxes()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterAxes ( std::vector< short > & cluster_axes )
inline

Gets the number of non-disambiguable axes that correspond to each centroid.

Parameters
[out] cluster_axes vector mapping each centroid to the number of signatures

Definition at line 266 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::cluster_axes_.

getClusterIndices()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterIndices ( std::vector< pcl::PointIndices > & indices )
inline

Gets the indices of the original point cloud used to compute the signatures.

Parameters
[out] indices vector of point indices

Definition at line 257 of file our_cvfh.h.

References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::clusters_.

getTransforms()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getTransforms ( std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > & trans )
inline

Returns the transformations aligning the point cloud to the corresponding SGURF.

Parameters
[out] trans vector of transformations

Definition at line 284 of file our_cvfh.h.

getValidTransformsVec()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getValidTransformsVec ( std::vector< bool > & valid )
inline

Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a valid SGURF.

Parameters
[out] valid vector of booleans

Definition at line 294 of file our_cvfh.h.

getViewPoint()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getViewPoint ( float & vpx,
float & vpy,
float & vpz
)
inline

Get the viewpoint.

Parameters
[out] vpx the X coordinate of the viewpoint
[out] vpy the Y coordinate of the viewpoint
[out] vpz the Z coordinate of the viewpoint

Definition at line 180 of file our_cvfh.h.

setAxisRatio()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setAxisRatio ( float f )
inline

Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible.

Parameters
[in] f the ratio between axes

Definition at line 303 of file our_cvfh.h.

setClusterTolerance()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setClusterTolerance ( float d )
inline

Sets max.

Euclidean distance between points to be added to the cluster

Parameters
[in] d the maximum Euclidean distance

Definition at line 212 of file our_cvfh.h.

setCurvatureThreshold()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setCurvatureThreshold ( float d )
inline

Sets curvature threshold for removing normals.

Parameters
[in] d the curvature threshold

Definition at line 230 of file our_cvfh.h.

setEPSAngleThreshold()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setEPSAngleThreshold ( float d )
inline

Sets max.

deviation of the normals between two points so they can be clustered together

Parameters
[in] d the maximum deviation

Definition at line 221 of file our_cvfh.h.

setMinAxisValue()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setMinAxisValue ( float f )
inline

Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition is difficult.

Parameters
[in] f the min axis value

Definition at line 312 of file our_cvfh.h.

setMinPoints()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setMinPoints ( std::size_t min )
inline

Set minimum amount of points for a cluster to be considered.

Parameters
[in] min the minimum amount of points to be set

Definition at line 239 of file our_cvfh.h.

setNormalizeBins()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setNormalizeBins ( bool normalize )
inline

Sets whether the signatures should be normalized or not.

Parameters
[in] normalize true if normalization is required, false otherwise

Definition at line 248 of file our_cvfh.h.

setRadiusNormals()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setRadiusNormals ( float radius_normals )
inline

Set the radius used to compute normals.

Parameters
[in] radius_normals the radius

Definition at line 169 of file our_cvfh.h.

setRefineClusters()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setRefineClusters ( float rc )
inline

Sets the refinement factor for the clusters.

Parameters
[in] rc the factor used to decide if a point is used to estimate a stable cluster

Definition at line 275 of file our_cvfh.h.

setViewPoint()

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::setViewPoint ( float vpx,
float vpy,
float vpz
)
inline

Set the viewpoint.

Parameters
[in] vpx the X coordinate of the viewpoint
[in] vpy the Y coordinate of the viewpoint
[in] vpz the Z coordinate of the viewpoint

Definition at line 158 of file our_cvfh.h.

sgurf()

template<typename PointInT , typename PointNT , typename PointOutT >
bool pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::sgurf ( Eigen::Vector3f & centroid,
Eigen::Vector3f & normal_centroid,
PointInTPtr & processed,
std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > & transformations,
PointInTPtr & grid,
pcl::PointIndices & indices
)

Computes SGURF.

Parameters
[in] centroid the centroid of the cluster
[in] normal_centroid the average of the normals
[in] processed the input cloud
[out] transformations the transformations aligning the cloud to the SGURF axes
[out] grid the cloud transformed internally
[in] indices the indices of the stable cluster

Definition at line 198 of file our_cvfh.hpp.

References pcl::demeanPointCloud(), pcl::getMaxDistance(), pcl::PointIndices::indices, and pcl::transformPointCloud().

Member Data Documentation

centroids_dominant_orientations_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_
protected

Centroids that were used to compute different OUR-CVFH descriptors.

Definition at line 394 of file our_cvfh.h.

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

cluster_axes_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
std::vector<short> pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::cluster_axes_
protected

Mapping from clusters to OUR-CVFH descriptors.

Definition at line 400 of file our_cvfh.h.

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

clusters_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
std::vector<pcl::PointIndices> pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::clusters_
protected

Indices to the points representing the stable clusters.

Definition at line 398 of file our_cvfh.h.

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

dominant_normals_

template<typename PointInT , typename PointNT , typename PointOutT = pcl::VFHSignature308>
std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_
protected

Normal centroids that were used to compute different OUR-CVFH descriptors.

Definition at line 396 of file our_cvfh.h.

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


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

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_o_u_r_c_v_f_h_estimation.html