Point Cloud Library (PCL) 1.12.0
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CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
#include <pcl/features/cvfh.h>
Public Member Functions | |
CVFHEstimation () | |
Empty constructor. | |
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. | |
void | setViewPoint (float vpx, float vpy, float vpz) |
Set the viewpoint. | |
void | setRadiusNormals (float radius_normals) |
Set the radius used to compute normals. | |
void | getViewPoint (float &vpx, float &vpy, float &vpz) |
Get the viewpoint. | |
void | getCentroidClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > ¢roids) |
Get the centroids used to compute different CVFH descriptors. | |
void | getCentroidNormalClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > ¢roids) |
Get the normal centroids used to compute different CVFH descriptors. | |
void | setClusterTolerance (float d) |
Sets max. | |
void | setEPSAngleThreshold (float d) |
Sets max. | |
void | setCurvatureThreshold (float d) |
Sets curvature threshold for removing normals. | |
void | setMinPoints (std::size_t min) |
Set minimum amount of points for a cluster to be considered. | |
void | setNormalizeBins (bool normalize) |
Sets whether if the CVFH signatures should be normalized or not. | |
void | compute (PointCloudOut &output) |
Overloaded computed method from pcl::Feature. | |
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FeatureFromNormals () | |
Empty constructor. | |
virtual | ~FeatureFromNormals () |
Empty destructor. | |
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. | |
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Feature () | |
Empty constructor. | |
virtual | ~Feature () |
Empty destructor. | |
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 () | |
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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. | |
Protected Attributes | |
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > | centroids_dominant_orientations_ |
Centroids that were used to compute different CVFH descriptors. | |
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > | dominant_normals_ |
Normal centroids that were used to compute different CVFH descriptors. | |
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PointCloudNConstPtr | normals_ |
A pointer to the input dataset that contains the point normals of the XYZ dataset. | |
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std::string | feature_name_ |
The feature name. | |
SearchMethodSurface | search_method_surface_ |
The search method template for points. | |
PointCloudInConstPtr | surface_ |
An input point cloud describing the surface that is to be used for nearest neighbors estimation. | |
KdTreePtr | tree_ |
A pointer to the spatial search object. | |
double | search_parameter_ |
The actual search parameter (from either search_radius_ or k_). | |
double | search_radius_ |
The nearest neighbors search radius for each point. | |
int | k_ |
The number of K nearest neighbors to use for each point. | |
bool | fake_surface_ |
If no surface is given, we use the input PointCloud as the surface. | |
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PointCloudConstPtr | input_ |
The input point cloud dataset. | |
IndicesPtr | indices_ |
A pointer to the vector of point indices to use. | |
bool | use_indices_ |
Set to true if point indices are used. | |
bool | fake_indices_ |
If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. | |
Additional Inherited Members | |
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virtual bool | initCompute () |
This method should get called before starting the actual computation. | |
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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. | |
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bool | initCompute () |
This method should get called before starting the actual computation. | |
bool | deinitCompute () |
This method should get called after finishing the actual computation. | |
CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in:
The suggested PointOutT is pcl::VFHSignature308.
using pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const CVFHEstimation<PointInT, PointNT, PointOutT> > |
using pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::KdTreePtr = typename pcl::search::Search<PointNormal>::Ptr |
using pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<CVFHEstimation<PointInT, PointNT, PointOutT> > |
using pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::VFHEstimator = pcl::VFHEstimation<PointInT, PointNT, pcl::VFHSignature308> |
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inline |
Empty constructor.
Definition at line 81 of file cvfh.h.
References pcl::Feature< PointInT, PointOutT >::feature_name_, pcl::Feature< PointInT, PointOutT >::k_, and pcl::Feature< PointInT, PointOutT >::search_radius_.
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::compute | ( | PointCloudOut & | output | ) |
Overloaded computed method from pcl::Feature.
[out] | output | the resultant point cloud model dataset containing the estimated features |
Definition at line 50 of file cvfh.hpp.
References pcl::Feature< PointInT, PointOutT >::deinitCompute().
void pcl::CVFHEstimation< 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.
[in] | cloud | pointcloud to be filtered |
[in] | indices_to_use | the 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 160 of file cvfh.hpp.
References pcl::ConstCloudIterator< PointT >::size().
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inline |
Get the centroids used to compute different CVFH descriptors.
[out] | centroids | vector to hold the centroids |
Definition at line 147 of file cvfh.h.
References pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_.
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inline |
Get the normal centroids used to compute different CVFH descriptors.
[out] | centroids | vector to hold the normal centroids |
Definition at line 157 of file cvfh.h.
References pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_.
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inline |
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protected |
Centroids that were used to compute different CVFH descriptors.
Definition at line 279 of file cvfh.h.
Referenced by pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidClusters().
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protected |
Normal centroids that were used to compute different CVFH descriptors.
Definition at line 281 of file cvfh.h.
Referenced by pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidNormalClusters().