Point Cloud Library (PCL)
1.14.1-dev
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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 |
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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, pcl::VFHSignature308 > > |
using | ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > > |
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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 | |
OURCVFHEstimation () | |
Empty constructor. More... | |
Eigen::Matrix4f | createTransFromAxes (Eigen::Vector3f &evx, Eigen::Vector3f &evy, Eigen::Vector3f &evz, Eigen::Affine3f &transformPC, Eigen::Matrix4f ¢er_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 ¢roid, 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 > > ¢roids) |
Get the centroids used to compute different CVFH descriptors. More... | |
void | getCentroidNormalClusters (std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > ¢roids) |
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... | |
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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 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... | |
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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... | |
Additional Inherited Members | |
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virtual bool | initCompute () |
This method should get called before starting the actual computation. 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... | |
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:
Definition at line 59 of file our_cvfh.h.
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const OURCVFHEstimation<PointInT, PointNT, PointOutT> > |
Definition at line 63 of file our_cvfh.h.
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::KdTreePtr = typename pcl::search::Search<PointNormal>::Ptr |
Definition at line 73 of file our_cvfh.h.
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut |
Definition at line 72 of file our_cvfh.h.
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::PointInTPtr = typename pcl::PointCloud<PointInT>::Ptr |
Definition at line 74 of file our_cvfh.h.
using pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<OURCVFHEstimation<PointInT, PointNT, PointOutT> > |
Definition at line 62 of file our_cvfh.h.
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Empty constructor.
Definition at line 76 of file our_cvfh.h.
References pcl::Feature< PointInT, PointOutT >::feature_name_, pcl::Feature< PointInT, PointOutT >::k_, and pcl::Feature< PointInT, PointOutT >::search_radius_.
void pcl::OURCVFHEstimation< 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 53 of file our_cvfh.hpp.
References pcl::PointCloud< PointT >::clear(), pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::resize(), and pcl::PointCloud< PointT >::width.
void pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution | ( | PointInTPtr & | processed, |
PointCloudOut & | output, | ||
std::vector< pcl::PointIndices > & | cluster_indices | ||
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Computes SGURF and the shape distribution based on the selected SGURF.
[in] | processed | the input cloud |
[out] | output | the resulting signature |
[in] | cluster_indices | the indices of the stable cluster |
Definition at line 383 of file our_cvfh.hpp.
References pcl::PointCloud< PointT >::clear(), pcl::PointCloud< PointT >::empty(), pcl::getMaxDistance(), pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::push_back(), pcl::PointCloud< PointT >::resize(), pcl::PointCloud< PointT >::size(), pcl::transformPointCloud(), and pcl::PointCloud< PointT >::width.
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Creates an affine transformation from the RF axes.
[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.
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 | ||
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Removes normals with high curvature caused by real edges or noisy data.
[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 170 of file our_cvfh.hpp.
References pcl::PointCloud< PointT >::size().
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Get the centroids used to compute different CVFH descriptors.
[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_.
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Get the normal centroids used to compute different CVFH descriptors.
[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_.
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Gets the number of non-disambiguable axes that correspond to each centroid.
[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_.
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Gets the indices of the original point cloud used to compute the signatures.
[out] | indices | vector of point indices |
Definition at line 257 of file our_cvfh.h.
References pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::clusters_.
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Returns the transformations aligning the point cloud to the corresponding SGURF.
[out] | trans | vector of transformations |
Definition at line 284 of file our_cvfh.h.
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Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a valid SGURF.
[out] | valid | vector of booleans |
Definition at line 294 of file our_cvfh.h.
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Get the viewpoint.
[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.
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Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible.
[in] | f | the ratio between axes |
Definition at line 303 of file our_cvfh.h.
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Sets max.
Euclidean distance between points to be added to the cluster
[in] | d | the maximum Euclidean distance |
Definition at line 212 of file our_cvfh.h.
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Sets curvature threshold for removing normals.
[in] | d | the curvature threshold |
Definition at line 230 of file our_cvfh.h.
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Sets max.
deviation of the normals between two points so they can be clustered together
[in] | d | the maximum deviation |
Definition at line 221 of file our_cvfh.h.
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Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition is difficult.
[in] | f | the min axis value |
Definition at line 312 of file our_cvfh.h.
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Set minimum amount of points for a cluster to be considered.
[in] | min | the minimum amount of points to be set |
Definition at line 239 of file our_cvfh.h.
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Sets whether the signatures should be normalized or not.
[in] | normalize | true if normalization is required, false otherwise |
Definition at line 248 of file our_cvfh.h.
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Set the radius used to compute normals.
[in] | radius_normals | the radius |
Definition at line 169 of file our_cvfh.h.
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Sets the refinement factor for the clusters.
[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.
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Set the viewpoint.
[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.
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.
[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 200 of file our_cvfh.hpp.
References pcl::demeanPointCloud(), pcl::getMaxDistance(), pcl::PointIndices::indices, and pcl::transformPointCloud().
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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().
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Mapping from clusters to OUR-CVFH descriptors.
Definition at line 400 of file our_cvfh.h.
Referenced by pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::getClusterAxes().
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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().
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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().