Table of Contents

Class KMeansIndexParams

Namespace
OpenCvSharp.Flann
Assembly
OpenCvSharp.dll

When passing an object of this type the index constructed will be a hierarchical k-means tree.

public class KMeansIndexParams : IndexParams, IDisposable, ICvPtrHolder
Inheritance
KMeansIndexParams
Implements
Inherited Members

Constructors

KMeansIndexParams(Ptr) 

protected KMeansIndexParams(Ptr ptrObj)

Parameters

ptrObj Ptr

KMeansIndexParams(int, int, FlannCentersInit, float)

Constructor

public KMeansIndexParams(int branching = 32, int iterations = 11, FlannCentersInit centersInit = FlannCentersInit.Random, float cbIndex = 0.2)

Parameters

branching int

The branching factor to use for the hierarchical k-means tree

iterations int

The maximum number of iterations to use in the k-means clustering stage when building the k-means tree. A value of -1 used here means that the k-means clustering should be iterated until convergence

centersInit FlannCentersInit

The algorithm to use for selecting the initial centers when performing a k-means clustering step.

cbIndex float

This parameter (cluster boundary index) influences the way exploration is performed in the hierarchical kmeans tree. When cb_index is zero the next kmeans domain to be explored is choosen to be the one with the closest center. A value greater then zero also takes into account the size of the domain.

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