CGAL 5.4 - Classification
CGAL::Classification Namespace Reference

Namespaces

 ETHZ
 
 Feature
 
 OpenCV
 

Classes

class  Classifier
 Concept describing a classifier used by classification functions (see CGAL::Classification::classify(), CGAL::Classification::classify_with_local_smoothing() and CGAL::Classification::classify_with_graphcut()). More...
 
class  Cluster
 Class that represent a cluster of items to be classified as a single atomic object. More...
 
class  Evaluation
 Class to compute several measurements to evaluate the quality of a classification output. More...
 
class  Face_descriptor_to_center_of_mass_map
 Property map that constructs the center of mass of the face of a mesh on-the-fly. More...
 
class  Face_descriptor_to_face_descriptor_with_bbox_map
 Property map that constructs a face descriptor with a bbox() method from a face descriptor. More...
 
class  Feature_base
 Abstract class describing a classification feature that associates a scalar value to each item of the classification input. More...
 
class  Feature_handle
 Handle to a Feature_base. More...
 
class  Feature_set
 sets of features (see Feature_base) used as input by classification algorithms. More...
 
class  Label
 Classification label (for example: vegetation, ground, etc.). More...
 
class  Label_handle
 Handle to a classification Label. More...
 
class  Label_set
 sets of Label used as input by classification algorithms. More...
 
class  Local_eigen_analysis
 Class that precomputes and stores the eigenvectors and eigenvalues of the covariance matrices of all points of a point set using a local neighborhood. More...
 
class  Mesh_feature_generator
 generates a set of generic features for surface mesh classification. More...
 
class  Mesh_neighborhood
 Class that generates models of NeighborQuery based on an input mesh. More...
 
class  NeighborQuery
 Concept describing a neighbor query used for classification. More...
 
class  Planimetric_grid
 Class that precomputes a 2D planimetric grid. More...
 
class  Point_set_feature_generator
 generates a set of generic features for point set classification. More...
 
class  Point_set_neighborhood
 Class that precomputes spatial searching structures for an input point set and gives access to the local neighborhood of a point as a set of indices. More...
 
class  Sum_of_weighted_features_classifier
 Classifier based on the sum of weighted features with user-defined effects on labels. More...
 

Functions

template<typename ItemRange , typename ItemMap , typename IndexMap >
std::size_t create_clusters_from_indices (const ItemRange &range, ItemMap item_map, IndexMap index_map, std::vector< Cluster< ItemRange, ItemMap > > &clusters)
 Given a set of cluster indices, segments the input range into Cluster objects. More...
 
template<typename FeatureType >
FeatureType * feature_cast (Feature_handle fh)
 casts a feature handle to a specialized feature pointer.
 
template<typename ConcurrencyTag , typename ItemRange , typename Classifier , typename LabelIndexRange >
void classify (const ItemRange &input, const Label_set &labels, const Classifier &classifier, LabelIndexRange &output)
 runs the classification algorithm without any regularization. More...
 
template<typename ConcurrencyTag , typename ItemRange , typename ItemMap , typename NeighborQuery , typename Classifier , typename LabelIndexRange >
void classify_with_local_smoothing (const ItemRange &input, const ItemMap item_map, const Label_set &labels, const Classifier &classifier, const NeighborQuery &neighbor_query, LabelIndexRange &output)
 runs the classification algorithm with a local smoothing. More...
 
template<typename ConcurrencyTag , typename ItemRange , typename ItemMap , typename NeighborQuery , typename Classifier , typename LabelIndexRange >
void classify_with_graphcut (const ItemRange &input, const ItemMap item_map, const Label_set &labels, const Classifier &classifier, const NeighborQuery &neighbor_query, const float strength, const std::size_t min_number_of_subdivisions, LabelIndexRange &output)
 runs the classification algorithm with a global regularization based on a graph cut. More...