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 <cvfh.h>
Public Types | |
typedef boost::shared_ptr < const CVFHEstimation < PointInT, PointNT, PointOutT > > | ConstPtr |
typedef pcl::search::Search < PointNormal >::Ptr | KdTreePtr |
typedef Feature< PointInT, PointOutT >::PointCloudOut | PointCloudOut |
typedef boost::shared_ptr < CVFHEstimation< PointInT, PointNT, PointOutT > > | Ptr |
typedef pcl::VFHEstimation < PointInT, PointNT, pcl::VFHSignature308 > | VFHEstimator |
Public Member Functions | |
void | compute (PointCloudOut &output) |
Overloaded computed method from pcl::Feature. | |
CVFHEstimation () | |
Empty constructor. | |
void | filterNormalsWithHighCurvature (const pcl::PointCloud< PointNT > &cloud, std::vector< int > &indices_to_use, std::vector< int > &indices_out, std::vector< int > &indices_in, float threshold) |
Removes normals with high curvature caused by real edges or noisy data. | |
void | getCentroidClusters (std::vector< Eigen::Vector3f > ¢roids) |
Get the centroids used to compute different CVFH descriptors. | |
void | getCentroidNormalClusters (std::vector< Eigen::Vector3f > ¢roids) |
Get the normal centroids used to compute different CVFH descriptors. | |
void | getViewPoint (float &vpx, float &vpy, float &vpz) |
Get the viewpoint. | |
void | setClusterTolerance (float d) |
Sets max. Euclidean distance between points to be added to the cluster. | |
void | setCurvatureThreshold (float d) |
Sets curvature threshold for removing normals. | |
void | setEPSAngleThreshold (float d) |
Sets max. deviation of the normals between two points so they can be clustered together. | |
void | setMinPoints (size_t min) |
Set minimum amount of points for a cluster to be considered. | |
void | setNormalizeBins (bool normalize) |
Sets wether if the CVFH signatures should be normalized or not. | |
void | setRadiusNormals (float radius_normals) |
Set the radius used to compute normals. | |
void | setViewPoint (float vpx, float vpy, float vpz) |
Set the viewpoint. | |
Protected Attributes | |
std::vector< Eigen::Vector3f > | centroids_dominant_orientations_ |
Centroids that were used to compute different CVFH descriptors. | |
std::vector< Eigen::Vector3f > | dominant_normals_ |
Normal centroids that were used to compute different CVFH descriptors. | |
Private Member Functions | |
void | computeFeature (PointCloudOut &output) |
Estimate the Clustered Viewpoint Feature Histograms (CVFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () | |
void | extractEuclideanClustersSmooth (const pcl::PointCloud< pcl::PointNormal > &cloud, const pcl::PointCloud< pcl::PointNormal > &normals, float tolerance, const pcl::search::Search< pcl::PointNormal >::Ptr &tree, std::vector< pcl::PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)()) |
Region growing method using Euclidean distances and neighbors normals to add points to a region. | |
Private Attributes | |
float | cluster_tolerance_ |
allowed Euclidean distance between points to be added to the cluster. | |
float | curv_threshold_ |
Curvature threshold for removing normals. | |
float | eps_angle_threshold_ |
deviation of the normals between two points so they can be clustered together. | |
float | leaf_size_ |
Size of the voxels after voxel gridding. IMPORTANT: Must match the voxel size of the training data or the normalize_bins_ flag must be set to true. | |
size_t | min_points_ |
Minimum amount of points in a clustered region to be considered stable for CVFH computation. | |
bool | normalize_bins_ |
Wether to normalize the signatures or not. Default: false. | |
float | radius_normals_ |
Radius for the normals computation. | |
float | vpx_ |
Values describing the viewpoint ("pinhole" camera model assumed). By default, the viewpoint is set to 0,0,0. | |
float | vpy_ |
float | vpz_ |
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.
typedef boost::shared_ptr<const CVFHEstimation<PointInT, PointNT, PointOutT> > pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr |
Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.
typedef pcl::search::Search<PointNormal>::Ptr pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::KdTreePtr |
Reimplemented from pcl::Feature< PointInT, PointOutT >.
typedef Feature<PointInT, PointOutT>::PointCloudOut pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut |
Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.
typedef boost::shared_ptr<CVFHEstimation<PointInT, PointNT, PointOutT> > pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::Ptr |
Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.
typedef pcl::VFHEstimation<PointInT, PointNT, pcl::VFHSignature308> pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::VFHEstimator |
pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::CVFHEstimation | ( | ) | [inline] |
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 |
Reimplemented from pcl::Feature< PointInT, PointOutT >.
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::computeFeature | ( | PointCloudOut & | output | ) | [private, virtual] |
Estimate the Clustered Viewpoint Feature Histograms (CVFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface ()
[out] | output | the resultant point cloud model dataset that contains the CVFH feature estimates |
Implements pcl::Feature< PointInT, PointOutT >.
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::extractEuclideanClustersSmooth | ( | const pcl::PointCloud< pcl::PointNormal > & | cloud, |
const pcl::PointCloud< pcl::PointNormal > & | normals, | ||
float | tolerance, | ||
const pcl::search::Search< pcl::PointNormal >::Ptr & | tree, | ||
std::vector< pcl::PointIndices > & | clusters, | ||
double | eps_angle, | ||
unsigned int | min_pts_per_cluster = 1 , |
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unsigned int | max_pts_per_cluster = (std::numeric_limits<int>::max) () |
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) | [private] |
Region growing method using Euclidean distances and neighbors normals to add points to a region.
[in] | cloud | point cloud to split into regions |
[in] | normals | are the normals of cloud |
[in] | tolerance | is the allowed Euclidean distance between points to be added to the cluster |
[in] | tree | is the spatial search structure for nearest neighbour search |
[out] | clusters | vector of indices representing the clustered regions |
[in] | eps_angle | deviation of the normals between two points so they can be clustered together |
[in] | min_pts_per_cluster | minimum cluster size. (default: 1 point) |
[in] | max_pts_per_cluster | maximum cluster size. (default: all the points) |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature | ( | const pcl::PointCloud< PointNT > & | cloud, |
std::vector< int > & | indices_to_use, | ||
std::vector< int > & | indices_out, | ||
std::vector< int > & | indices_in, | ||
float | threshold | ||
) |
Removes normals with high curvature caused by real edges or noisy data.
[in] | cloud | pointcloud to be filtered |
[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 |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidClusters | ( | std::vector< Eigen::Vector3f > & | centroids | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::getCentroidNormalClusters | ( | std::vector< Eigen::Vector3f > & | centroids | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::getViewPoint | ( | float & | vpx, |
float & | vpy, | ||
float & | vpz | ||
) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setClusterTolerance | ( | float | d | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setCurvatureThreshold | ( | float | d | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setEPSAngleThreshold | ( | float | d | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setMinPoints | ( | size_t | min | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setNormalizeBins | ( | bool | normalize | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setRadiusNormals | ( | float | radius_normals | ) | [inline] |
void pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::setViewPoint | ( | float | vpx, |
float | vpy, | ||
float | vpz | ||
) | [inline] |
std::vector<Eigen::Vector3f> pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::centroids_dominant_orientations_ [protected] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::cluster_tolerance_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::curv_threshold_ [private] |
std::vector<Eigen::Vector3f> pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::dominant_normals_ [protected] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::eps_angle_threshold_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::leaf_size_ [private] |
size_t pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::min_points_ [private] |
bool pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::normalize_bins_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::radius_normals_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::vpx_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::vpy_ [private] |
float pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::vpz_ [private] |