CGAL 4.12.2 - Classification
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CGAL::Classification::classify()
CGAL::Classification::classify_with_local_smoothing()
CGAL::Classification::classify_with_graphcut()
CGAL::Classification::Sum_of_weighted_features_classifier
CGAL::Classification::ETHZ_random_forest_classifier
CGAL::Classification::OpenCV_random_forest_classifier
CGAL::Classification::Local_eigen_analysis
CGAL::Classification::Planimetric_grid<Geom_traits, PointRange, PointMap>
CGAL::Classification::Point_set_feature_generator<Geom_traits, PointRange, PointMap, ConcurrencyTag, DiagonalizeTraits>
CGAL::Classification::Point_set_neighborhood<Geom_traits, PointRange, PointMap>
CGAL::Classification::Evaluation
CGAL::Classification::Feature_base
CGAL::Classification::Feature_handle
CGAL::Classification::Feature_set
CGAL::Classification::Feature::Anisotropy
CGAL::Classification::Feature::Distance_to_plane<PointRange, PointMap>
CGAL::Classification::Feature::Echo_scatter<Geom_traits, PointRange, PointMap, EchoMap>
CGAL::Classification::Feature::Eigentropy
CGAL::Classification::Feature::Elevation<Geom_traits, PointRange, PointMap>
CGAL::Classification::Feature::Hsv<Geom_traits, PointRange, ColorMap>
CGAL::Classification::Feature::Linearity
CGAL::Classification::Feature::Omnivariance
CGAL::Classification::Feature::Planarity
CGAL::Classification::Feature::Simple_feature<InputRange, PropertyMap>
CGAL::Classification::Feature::Sphericity
CGAL::Classification::Feature::Sum_eigenvalues
CGAL::Classification::Feature::Surface_variation
CGAL::Classification::Feature::Vertical_dispersion<Geom_traits, PointRange, PointMap>
CGAL::Classification::Feature::Verticality<Geom_traits>
Modules | |
Concepts | |
Main Functions | |
Functions that perform classification based on a set of labels and a classifier, with or without regularization. | |
Classifiers | |
Classifiers are functors that, given a label set and an input item, associate this input item with an energy for each label. | |
Data Structures | |
Useful data structures that are used to compute features (computation of eigenvalues, for example) and to regularize classification (neighborhood). | |
Label | |
A label represents how an item should be classified, for example: vegetation, building, road, etc. | |
Feature | |
Features are defined as scalar fields that associates each input item with a specific value. | |
Predefined Features | |
CGAL provides some predefined features that are relevant for classification of point sets. | |