CGAL 6.2 - Classification

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Modules
Reference Manual

##

Simon Giraudot and 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-12-26a
License: GPL
Windows Demo: CGAL Lab

## 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::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.