Classification Reference

Simon Giraudot, Florent Lafarge

This component implements an algorithm that classifies a data set into a user-defined set of labels (such as ground, vegetation, buildings, etc.). A flexible API is provided so that users can classify any type of data, compute their own local features on the input data set, and define their own labels.

Introduced in: CGAL 4.12
Depends on: CGAL and Solvers, dD Spatial Searching
BibTeX: cgal:lm-clscm-12-20b
License: GPL
Windows Demo: Operations on Polyhedra
Common Demo Dlls: dlls

Classified Reference Pages

Concepts

• CGAL::Classification::Classifier
• CGAL::Classification::NeighborQuery

Main Functions

• CGAL::Classification::classify()
• CGAL::Classification::classify_with_local_smoothing()
• CGAL::Classification::classify_with_graphcut()

Classifiers

• CGAL::Classification::ETHZ::Random_forest_classifier
• CGAL::Classification::OpenCV::Random_forest_classifier
• CGAL::Classification::TensorFlow::Neural_network_classifier<ActivationFunction>
• CGAL::Classification::Sum_of_weighted_features_classifier

Common Data Structures

• CGAL::Classification::Local_eigen_analysis
• CGAL::Classification::Planimetric_grid<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Evaluation

Label

• CGAL::Classification::Label
• CGAL::Classification::Label_handle
• CGAL::Classification::Label_set

Feature

• CGAL::Classification::Feature_base
• CGAL::Classification::Feature_handle
• CGAL::Classification::Feature_set

Predefined Features

• CGAL::Classification::Feature::Color_channel<GeomTraits, PointRange, ColorMap>
• CGAL::Classification::Feature::Distance_to_plane<PointRange, PointMap>
• CGAL::Classification::Feature::Echo_scatter<GeomTraits, PointRange, PointMap, EchoMap>
• CGAL::Classification::Feature::Eigenvalue
• CGAL::Classification::Feature::Elevation<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Feature::Height_above<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Feature::Height_below<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Feature::Simple_feature<InputRange, PropertyMap>
• CGAL::Classification::Feature::Vertical_dispersion<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Feature::Vertical_range<GeomTraits, PointRange, PointMap>
• CGAL::Classification::Feature::Verticality<GeomTraits>

Point Set Classification

• CGAL::Classification::Point_set_feature_generator<GeomTraits, PointRange, PointMap, ConcurrencyTag, DiagonalizeTraits>
• CGAL::Classification::Point_set_neighborhood<GeomTraits, PointRange, PointMap>

Mesh Classification

• CGAL::Classification::Mesh_feature_generator<GeomTraits, FaceGraph, PointMap, ConcurrencyTag, DiagonalizeTraits>
• CGAL::Classification::Mesh_neighborhood<FaceListGraph>
• CGAL::Classification::Face_descriptor_to_center_of_mass_map<FaceListGraph, VertexPointMap>
• CGAL::Classification::Face_descriptor_to_face_descriptor_with_bbox_map<FaceListGraph, VertexPointMap>

Cluster Classification

• CGAL::Classification::Cluster<ItemRange, ItemMap>
• CGAL::Classification::create_clusters_from_indices()
• CGAL::Classification::Feature::Cluster_mean_of_feature
• CGAL::Classification::Feature::Cluster_variance_of_feature
• CGAL::Classification::Feature::Cluster_size
• CGAL::Classification::Feature::Cluster_vertical_extent

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.
	Common Data Structures
	Useful data structures that are used to compute features (computation of eigenvalues, for example).
	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.
	Point Set Classification
	Data structures specialized to classify point sets.
	Mesh Classification
	Data structures specialized to classify surface meshes.
	Cluster Classification
	Data structures specialized to classify clusters.