\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.12.2 - Classification
CGAL::Classification::Feature::Eigentropy Class Reference

#include <CGAL/Classification/Feature/Eigen.h>

Inherits from

CGAL::Classification::Feature_base.

Definition

Feature based on the eigenvalues of the covariance matrix of a local neighborhood.

Eigentropy is defined, for the 3 eigenvalues \(\lambda_1 \ge \lambda_2 \ge \lambda_3 \ge 0\), as:

\[ - \sum_{i=1}^3 \lambda_i \times \log{\lambda_i} \]

Its default name is "eigentropy".

Public Member Functions

template<typename InputRange >
 Eigentropy (const InputRange &input, const Local_eigen_analysis &eigen)
 Constructs the feature. More...
 
- Public Member Functions inherited from CGAL::Classification::Feature_base
const std::string & name () const
 Returns the name of the feature (initialized to abstract_feature for Feature_base).
 
void set_name (const std::string &name)
 Changes the name of the feature.
 
virtual float value (std::size_t index)=0
 Returns the value taken by the feature for at the item for the item at position index. More...
 

Constructor & Destructor Documentation

◆ Eigentropy()

template<typename InputRange >
CGAL::Classification::Feature::Eigentropy::Eigentropy ( const InputRange &  input,
const Local_eigen_analysis eigen 
)

Constructs the feature.

Parameters
inputpoint range.
eigenclass with precomputed eigenvectors and eigenvalues.