43 #include <pcl/features/feature.h>
58 template<
typename Po
intInT,
typename Po
intNT,
typename Po
intOutT = pcl::VFHSignature308>
62 using Ptr = shared_ptr<OURCVFHEstimation<PointInT, PointNT, PointOutT> >;
63 using ConstPtr = shared_ptr<const OURCVFHEstimation<PointInT, PointNT, PointOutT> >;
77 cluster_tolerance_ (leaf_size_ * 3),
78 radius_normals_ (leaf_size_ * 3)
83 refine_clusters_ = 1.f;
84 min_axis_value_ = 0.925f;
96 inline Eigen::Matrix4f
97 createTransFromAxes (Eigen::Vector3f & evx, Eigen::Vector3f & evy, Eigen::Vector3f & evz, Eigen::Affine3f & transformPC,
98 Eigen::Matrix4f & center_mat)
100 Eigen::Matrix4f trans;
101 trans.setIdentity (4, 4);
102 trans (0, 0) = evx (0, 0);
103 trans (1, 0) = evx (1, 0);
104 trans (2, 0) = evx (2, 0);
105 trans (0, 1) = evy (0, 0);
106 trans (1, 1) = evy (1, 0);
107 trans (2, 1) = evy (2, 0);
108 trans (0, 2) = evz (0, 0);
109 trans (1, 2) = evz (1, 0);
110 trans (2, 2) = evz (2, 0);
112 Eigen::Matrix4f homMatrix = Eigen::Matrix4f ();
113 homMatrix.setIdentity (4, 4);
114 homMatrix = transformPC.matrix ();
116 Eigen::Matrix4f trans_copy = trans.inverse ();
117 trans = trans_copy * center_mat * homMatrix;
138 sgurf (Eigen::Vector3f & centroid, Eigen::Vector3f & normal_centroid,
PointInTPtr & processed, std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > & transformations,
171 radius_normals_ = radius_normals;
191 getCentroidClusters (std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > & centroids)
194 centroids.push_back (centroids_dominant_orientation);
204 centroids.push_back (dominant_normal);
214 cluster_tolerance_ = d;
223 eps_angle_threshold_ = d;
250 normalize_bins_ = normalize;
277 refine_clusters_ = rc;
284 getTransforms (std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > & trans)
296 valid = valid_transforms_;
327 float vpx_{0.0f}, vpy_{0.0f}, vpz_{0.0f};
332 float leaf_size_{0.005f};
335 bool normalize_bins_{
false};
338 float curv_threshold_{0.03f};
341 float cluster_tolerance_;
344 float eps_angle_threshold_{0.125f};
349 std::size_t min_points_{50};
352 float radius_normals_;
355 float refine_clusters_;
357 std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > transforms_;
358 std::vector<bool> valid_transforms_;
361 float min_axis_value_;
389 std::vector<pcl::PointIndices> &clusters,
double eps_angle,
unsigned int min_pts_per_cluster = 1,
390 unsigned int max_pts_per_cluster = (std::numeric_limits<int>::max) ());
404 #ifdef PCL_NO_PRECOMPILE
405 #include <pcl/features/impl/our_cvfh.hpp>
void compute(PointCloudOut &output)
Overloaded computed method from pcl::Feature.
shared_ptr< PointCloud< PointT > > Ptr
void getTransforms(std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &trans)
Returns the transformations aligning the point cloud to the corresponding SGURF.
void setMinPoints(std::size_t min)
Set minimum amount of points for a cluster to be considered.
typename KdTree::Ptr KdTreePtr
std::string feature_name_
The feature name.
int k_
The number of K nearest neighbors to use for each point.
typename pcl::PointCloud< PointInT >::Ptr PointInTPtr
void computeRFAndShapeDistribution(PointInTPtr &processed, PointCloudOut &output, std::vector< pcl::PointIndices > &cluster_indices)
Computes SGURF and the shape distribution based on the selected SGURF.
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > centroids_dominant_orientations_
Centroids that were used to compute different OUR-CVFH descriptors.
void setNormalizeBins(bool normalize)
Sets whether the signatures should be normalized or not.
void getClusterIndices(std::vector< pcl::PointIndices > &indices)
Gets the indices of the original point cloud used to compute the signatures.
void getCentroidNormalClusters(std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > ¢roids)
Get the normal centroids used to compute different CVFH descriptors.
shared_ptr< const Feature< PointInT, PointOutT > > ConstPtr
void setRadiusNormals(float radius_normals)
Set the radius used to compute normals.
void setRefineClusters(float rc)
Sets the refinement factor for the clusters.
std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > dominant_normals_
Normal centroids that were used to compute different OUR-CVFH descriptors.
void getValidTransformsVec(std::vector< bool > &valid)
Returns a boolean vector indicating of the transformation obtained by getTransforms() represents a va...
void setClusterTolerance(float d)
Sets max.
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
void getClusterAxes(std::vector< short > &cluster_axes)
Gets the number of non-disambiguable axes that correspond to each centroid.
void setAxisRatio(float f)
Sets the min axis ratio between the SGURF axes to decide if disambiguition is feasible.
IndicesAllocator<> Indices
Type used for indices in PCL.
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.
void getViewPoint(float &vpx, float &vpy, float &vpz)
Get the viewpoint.
shared_ptr< pcl::search::Search< PointT > > Ptr
Feature represents the base feature class.
void setEPSAngleThreshold(float d)
Sets max.
void getCentroidClusters(std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > ¢roids)
Get the centroids used to compute different CVFH descriptors.
void setViewPoint(float vpx, float vpy, float vpz)
Set the viewpoint.
OURCVFHEstimation()
Empty constructor.
void setMinAxisValue(float f)
Sets the min disambiguition axis value to generate several SGURFs for the cluster when disambiguition...
std::vector< short > cluster_axes_
Mapping from clusters to OUR-CVFH descriptors.
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 setCurvatureThreshold(float d)
Sets curvature threshold for removing normals.
std::vector< pcl::PointIndices > clusters_
Indices to the points representing the stable clusters.
OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram ...
double search_radius_
The nearest neighbors search radius for each point.
shared_ptr< Feature< PointInT, PointOutT > > Ptr
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.