pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC Struct Reference

This structure is used for determining the end of the k-means clustering process. More...

#include <implicit_shape_model.h>

List of all members.

Public Types
enum	{ COUNT = 1, EPS = 2 }
Public Member Functions
	TC (int type, int max_count, float epsilon)
	Termination criteria constructor.
Public Attributes
float	epsilon_
	Defines the accuracy for k-means clustering.
int	max_count_
	Defines maximum number of iterations for k-means clustering.
int	type_
	Flag that determines when the k-means clustering must be stopped. If type_ equals COUNT then it must be stopped when the max number of iterations will be reached. If type_ eaquals EPS then it must be stopped when the desired accuracy will be reached. These flags can be used together, in that case the clustering will be finished when one of these conditions will be reached.

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Detailed Description

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>
struct pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC

This structure is used for determining the end of the k-means clustering process.

Definition at line 278 of file implicit_shape_model.h.

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Member Enumeration Documentation

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>

anonymous enum

Enumerator:

COUNT
EPS

Definition at line 280 of file implicit_shape_model.h.

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Constructor & Destructor Documentation

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>

pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC::TC	(	int	type,
		int	max_count,
		float	epsilon
	)		[inline]

Termination criteria constructor.

Parameters:

[in]	type	defines the condition of termination(max iter., desired accuracy)
[in]	max_count	defines the max number of iterations
[in]	epsilon	defines the desired accuracy

Definition at line 291 of file implicit_shape_model.h.

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Member Data Documentation

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>

float pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC::epsilon_

Defines the accuracy for k-means clustering.

Definition at line 308 of file implicit_shape_model.h.

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>

int pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC::max_count_

Defines maximum number of iterations for k-means clustering.

Definition at line 305 of file implicit_shape_model.h.

template<int FeatureSize, typename PointT, typename NormalT = pcl::Normal>

int pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::TC::type_

Flag that determines when the k-means clustering must be stopped. If type_ equals COUNT then it must be stopped when the max number of iterations will be reached. If type_ eaquals EPS then it must be stopped when the desired accuracy will be reached. These flags can be used together, in that case the clustering will be finished when one of these conditions will be reached.

Definition at line 294 of file implicit_shape_model.h.

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The documentation for this struct was generated from the following file:

• implicit_shape_model.h