|
using | PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut |
|
using | PointCloudIn = typename Feature< PointInT, PointOutT >::PointCloudIn |
|
using | PointCloudInPtr = typename Feature< PointInT, PointOutT >::PointCloudInPtr |
|
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 > > |
|
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 |
|
|
| 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.
|
|
void | setNrSubdivisions (int nr_subdiv) |
| Set the number of subdivisions for the considered distance interval.
|
|
void | setPlaneRadius (double plane_radius) |
| Set the maximum radius, above which everything can be considered planar.
|
|
| 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.
|
|
| 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 ()
|
|
| 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.
|
|
|
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 ()
|
|
virtual bool | initCompute () |
| This method should get called before starting the actual computation.
|
|
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.
|
|
bool | initCompute () |
| This method should get called before starting the actual computation.
|
|
bool | deinitCompute () |
| This method should get called after finishing the actual computation.
|
|
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
- Template Parameters
-
Definition at line 72 of file grsd.h.
template<typename PointInT , typename PointNT , typename PointOutT >
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::PointCloud< PointT >::points, pcl::PCLBase< PointT >::setInputCloud(), pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >::setInputNormals(), pcl::VoxelGrid< PointT >::setLeafSize(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::setNrSubdivisions(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::setPlaneRadius(), pcl::Feature< PointInT, PointOutT >::setRadiusSearch(), pcl::VoxelGrid< PointT >::setSaveLeafLayout(), pcl::Feature< PointInT, PointOutT >::setSearchSurface(), and pcl::PointCloud< PointT >::size().
template<typename PointInT , typename PointNT , typename PointOutT >
Set the number of subdivisions for the considered distance interval.
This function configures the underlying RSDEstimation. For more info, see there. If this function is not called, the default from RSDEstimation is used.
- Parameters
-
[in] | nr_subdiv | the number of subdivisions |
Definition at line 115 of file grsd.h.
template<typename PointInT , typename PointNT , typename PointOutT >
void pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::setPlaneRadius |
( |
double |
plane_radius | ) |
|
|
inline |
Set the maximum radius, above which everything can be considered planar.
This function configures the underlying RSDEstimation. For more info, see there. If this function is not called, the default from RSDEstimation is used.
- Parameters
-
[in] | plane_radius | the new plane radius |
Definition at line 123 of file grsd.h.
template<typename PointInT , typename PointNT , typename PointOutT >
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 101 of file grsd.h.
References pcl::Feature< PointInT, PointOutT >::search_radius_.