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CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
#include <pcl/features/crh.h >
using
Ptr = shared_ptr< CRHEstimation < PointInT, PointNT, PointOutT > >
using
ConstPtr = shared_ptr< const CRHEstimation < PointInT, PointNT, PointOutT > >
using
PointCloudOut = typename Feature < PointInT, PointOutT >::PointCloudOut
using
PointCloudN = pcl::PointCloud < PointNT >
using
PointCloudNPtr = typename PointCloudN::Ptr
using
PointCloudNConstPtr = typename PointCloudN::ConstPtr
using
Ptr = shared_ptr< FeatureFromNormals < PointInT, PointNT, pcl::Histogram < 90 > > >
using
ConstPtr = shared_ptr< const FeatureFromNormals < PointInT, PointNT, pcl::Histogram < 90 > > >
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 > &)>
using
PointCloud = pcl::PointCloud < PointInT >
using
PointCloudPtr = typename PointCloud::Ptr
using
PointCloudConstPtr = typename PointCloud::ConstPtr
using
PointIndicesPtr = PointIndices::Ptr
using
PointIndicesConstPtr = PointIndices::ConstPtr
virtual bool
initCompute ()
This method should get called before starting the actual computation. More...
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...
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...
PointCloudNConstPtr
normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset. More...
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...
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...
template<typename PointInT, typename PointNT, typename PointOutT = pcl::Histogram<90>> class pcl::CRHEstimation< PointInT, PointNT, PointOutT > CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in:
CAD-Model Recognition and 6 DOF Pose Estimation A. Aldoma, N. Blodow, D. Gossow, S. Gedikli, R.B. Rusu, M. Vincze and G. Bradski ICCV 2011, 3D Representation and Recognition (3dRR11) workshop Barcelona, Spain, (2011) The suggested PointOutT is pcl::Histogram<90>. //dc (real) + 44 complex numbers (real, imaginary) + nyquist (real)
Author
Aitor Aldoma
Definition at line 60 of file crh.h .
ConstPtr template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
Definition at line 64 of file crh.h .
PointCloudOut template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
Definition at line 74 of file crh.h .
Ptr template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
Definition at line 63 of file crh.h .
CRHEstimation() template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
getViewPoint() template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
void pcl::CRHEstimation < 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 102 of file crh.h .
setCentroid() template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
void pcl::CRHEstimation < PointInT, PointNT, PointOutT >::setCentroid ( Eigen::Vector4f & centroid
)
inline
setViewPoint() template<typename PointInT , typename PointNT , typename PointOutT = pcl::Histogram<90>>
void pcl::CRHEstimation < 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 89 of file crh.h .
The documentation for this class was generated from the following files: