Point Cloud Library (PCL)
1.14.1
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ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
#include <pcl/features/3dsc.h>
Public Types | |
using | Ptr = shared_ptr< ShapeContext3DEstimation< PointInT, PointNT, PointOutT > > |
using | ConstPtr = shared_ptr< const ShapeContext3DEstimation< PointInT, PointNT, PointOutT > > |
using | PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut |
using | PointCloudIn = typename Feature< PointInT, PointOutT >::PointCloudIn |
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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 > > |
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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 > &)> |
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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 | |
ShapeContext3DEstimation (bool random=false) | |
Constructor. More... | |
~ShapeContext3DEstimation () override=default | |
std::size_t | getAzimuthBins () |
std::size_t | getElevationBins () |
std::size_t | getRadiusBins () |
void | setMinimalRadius (double radius) |
The minimal radius value for the search sphere (rmin) in the original paper. More... | |
double | getMinimalRadius () |
void | setPointDensityRadius (double radius) |
This radius is used to compute local point density density = number of points within this radius. More... | |
double | getPointDensityRadius () |
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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... | |
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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... | |
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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 | |
bool | initCompute () override |
Initialize computation by allocating all the intervals and the volume lookup table. More... | |
bool | computePoint (std::size_t index, const pcl::PointCloud< PointNT > &normals, float rf[9], std::vector< float > &desc) |
Estimate a descriptor for a given point. More... | |
void | computeFeature (PointCloudOut &output) override |
Estimate the actual feature. More... | |
float | rnd () |
Boost-based random number generator. More... | |
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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... | |
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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 | |
std::vector< float > | radii_interval_ |
Values of the radii interval. More... | |
std::vector< float > | theta_divisions_ |
Theta divisions interval. More... | |
std::vector< float > | phi_divisions_ |
Phi divisions interval. More... | |
std::vector< float > | volume_lut_ |
Volumes look up table. More... | |
std::size_t | azimuth_bins_ {12} |
Bins along the azimuth dimension. More... | |
std::size_t | elevation_bins_ {11} |
Bins along the elevation dimension. More... | |
std::size_t | radius_bins_ {15} |
Bins along the radius dimension. More... | |
double | min_radius_ {0.1} |
Minimal radius value. More... | |
double | point_density_radius_ {0.2} |
Point density radius. More... | |
std::size_t | descriptor_length_ {} |
Descriptor length. More... | |
std::mt19937 | rng_ |
Random number generator algorithm. More... | |
std::uniform_real_distribution< float > | rng_dist_ |
Random number generator distribution. More... | |
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PointCloudNConstPtr | normals_ |
A pointer to the input dataset that contains the point normals of the XYZ dataset. More... | |
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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... | |
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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... | |
ShapeContext3DEstimation implements the 3D shape context descriptor as described in:
The suggested PointOutT is pcl::ShapeContext1980
using pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const ShapeContext3DEstimation<PointInT, PointNT, PointOutT> > |
using pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn |
using pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut |
using pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<ShapeContext3DEstimation<PointInT, PointNT, PointOutT> > |
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Constructor.
[in] | random | If true the random seed is set to current time, else it is set to 12345 prior to computing the descriptor (used to select X axis) |
Definition at line 95 of file 3dsc.h.
References pcl::Feature< PointInT, PointOutT >::feature_name_, pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::rng_, and pcl::Feature< PointInT, PointOutT >::search_radius_.
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Estimate the actual feature.
[out] | output | the resultant feature |
Definition at line 255 of file 3dsc.hpp.
References pcl::isFinite().
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Estimate a descriptor for a given point.
[in] | index | the index of the point to estimate a descriptor for |
[in] | normals | a pointer to the set of normals |
[out] | rf | the reference frame |
[out] | desc | the resultant estimated descriptor |
–— Compute current neighbour polar coordinates –— Get distance between the neighbour and the origin
Project point into the tangent plane
Normalize to compute the dot product
Compute the angle between the projection and the x axis in the interval [0,360]
Compute the angle between the neighbour and the z axis (normal) in the interval [0, 180]
Accumulate w into correspondent Bin(j,k,l)
Definition at line 133 of file 3dsc.hpp.
References pcl::utils::equal(), pcl::isNormalFinite(), pcl::geometry::project(), and pcl::rad2deg().
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Definition at line 123 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::azimuth_bins_.
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Definition at line 130 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::elevation_bins_.
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Definition at line 147 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::min_radius_.
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Definition at line 158 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::point_density_radius_.
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Definition at line 137 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::radius_bins_.
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Initialize computation by allocating all the intervals and the volume lookup table.
Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.
Definition at line 53 of file 3dsc.hpp.
References pcl::deg2rad().
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The minimal radius value for the search sphere (rmin) in the original paper.
[in] | radius | the desired minimal radius |
Definition at line 143 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::min_radius_.
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This radius is used to compute local point density density = number of points within this radius.
[in] | radius | value of the point density search radius |
Definition at line 154 of file 3dsc.h.
References pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::point_density_radius_.
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Bins along the azimuth dimension.
Definition at line 195 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::getAzimuthBins().
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Bins along the elevation dimension.
Definition at line 198 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::getElevationBins().
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Minimal radius value.
Definition at line 204 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::getMinimalRadius(), and pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::setMinimalRadius().
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Point density radius.
Definition at line 207 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::getPointDensityRadius(), and pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::setPointDensityRadius().
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Bins along the radius dimension.
Definition at line 201 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::getRadiusBins().
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Random number generator algorithm.
Definition at line 213 of file 3dsc.h.
Referenced by pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::ShapeContext3DEstimation().
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