\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.13 - Classification
Class and Concept List
Here is the list of all concepts and classes of this package. Classes are inside the namespace CGAL. Concepts are in the global namespace.
[detail level 1234]
 NCGAL
 NClassification
 NFeature
 CCluster_mean_of_featureFeature that computes the mean values of an itemwise feature over the respective items of clusters
 CCluster_sizeFeature that returns the size of each cluster
 CCluster_variance_of_featureFeature that computes the variance values of an itemwise feature over the respective items of clusters
 CCluster_vertical_extentFeature that returns the length of the smallest interval on the Z axis that contains all the items of a cluster
 CColor_channelFeature based on HSV colorimetric information
 CDistance_to_planeFeature based on local distance to a fitted plane
 CEcho_scatterFeature based on echo scatter
 CEigenvalueFeature based on the eigenvalues of the covariance matrix of a local neighborhood
 CElevationFeature based on local elevation
 CSimple_featureFeature based on a user-defined scalar field
 CVertical_dispersionFeature based on local vertical dispersion of points
 CVerticalityFeature based on local verticality
 CClassifierConcept describing a classifier used by classification functions (see CGAL::Classification::classify(), CGAL::Classification::classify_with_local_smoothing() and CGAL::Classification::classify_with_graphcut())
 CClusterClass that represent a cluster of items to be classified as a single atomic object
 CETHZ_random_forest_classifierClassifier based on the ETH Zurich version of random forest algorithm [2]
 CEvaluationClass to compute several measurements to evaluate the quality of a classification output
 CFace_descriptor_to_center_of_mass_mapProperty map that constructs the center of mass of the face of a mesh on-the-fly
 CFace_descriptor_to_face_descriptor_with_bbox_mapProperty map that constructs a face descriptor with a bbox() method from a face descriptor
 Cface_descriptor_with_bboxFace descriptor with a precomputed bounding box
 CFeature_baseAbstract class describing a classification feature that associates a scalar value to each item of the classification input
 CFeature_handleHandle to a Feature_base
 CFeature_setSet of features (see Feature_base) used as input by classification algorithms
 CLabelClassification label (for example: vegetation, ground, etc.) defined as a set of relationships with classification features
 CLabel_handleHandle to a classification Label
 CLabel_setSet of Label used as input by classification algorithms
 CLocal_eigen_analysisClass that precomputes and stores the eigenvectors and eigenvalues of the covariance matrices of all points of a point set using a local neighborhood
 CMesh_feature_generatorGenerates a set of generic features for surface mesh classification
 CMesh_neighborhoodClass that generates models of NeighborQuery based on an input mesh
 CN_ring_neighbor_queryFunctor that computes the N-ring neighborhood of the face of an input mesh
 COne_ring_neighbor_queryFunctor that computes the 1-ring neighborhood of the face of an input mesh
 CNeighborQueryConcept describing a neighbor query used for classification
 COpenCV_random_forest_classifierClassifier based on the OpenCV version of random forest algorithm
 CPlanimetric_gridClass that precomputes a 2D planimetric grid
 CPoint_set_feature_generatorGenerates a set of generic features for point set classification
 CPoint_set_neighborhoodClass 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
 CK_neighbor_queryFunctor that computes the neighborhood of an input point with a fixed number of neighbors
 CSphere_neighbor_queryFunctor that computes the neighborhood of an input point defined as the points lying in a sphere of fixed radius centered at the input point
 CSum_of_weighted_features_classifierClassifier based on the sum of weighted features with user-defined effects on labels