GMM (Gaussian Mixture Models (GMM)) More...

#include "kmeans.h"

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Typedefs
typedef struct _VlGMM	VlGMM
typedef enum _VlGMMInitialization	VlGMMInitialization
	GMM initialization algorithms.
Enumerations
enum	_VlGMMInitialization { VlGMMKMeans, VlGMMRand, VlGMMCustom }
	GMM initialization algorithms. More...
Functions
VL_EXPORT double	vl_get_gmm_data_posteriors_d (double posteriors, vl_size numClusters, vl_size numData, double const priors, double const means, vl_size dimension, double const covariances, double const *data)
VL_EXPORT double	vl_get_gmm_data_posteriors_f (float posteriors, vl_size numClusters, vl_size numData, float const priors, float const means, vl_size dimension, float const covariances, float const *data)
VL_EXPORT void	vl_gmm_set_covariances (VlGMM self, void const covariances)
VL_EXPORT void	vl_gmm_set_means (VlGMM self, void const means)
VL_EXPORT void	vl_gmm_set_priors (VlGMM self, void const priors)
Create and destroy
VL_EXPORT VlGMM *	vl_gmm_new (vl_type dataType, vl_size dimension, vl_size numComponents)
	Create a new GMM object.
VL_EXPORT VlGMM *	vl_gmm_new_copy (VlGMM const *gmm)
VL_EXPORT void	vl_gmm_delete (VlGMM *self)
	Deletes a GMM object.
VL_EXPORT void	vl_gmm_reset (VlGMM *self)
	Reset state.
Basic data processing
VL_EXPORT double	vl_gmm_cluster (VlGMM self, void const data, vl_size numData)
Fine grained data processing
VL_EXPORT void	vl_gmm_init_with_rand_data (VlGMM self, void const data, vl_size numData)
VL_EXPORT void	vl_gmm_init_with_kmeans (VlGMM self, void const data, vl_size numData, VlKMeans *kmeansInit)
VL_EXPORT double	vl_gmm_em (VlGMM self, void const data, vl_size numData)
Set parameters
VL_EXPORT void	vl_gmm_set_num_repetitions (VlGMM *self, vl_size numRepetitions)
	Set maximum number of repetitions.
VL_EXPORT void	vl_gmm_set_max_num_iterations (VlGMM *self, vl_size maxNumIterations)
	Set maximum number of iterations.
VL_EXPORT void	vl_gmm_set_verbosity (VlGMM *self, int verbosity)
	Set verbosity level.
VL_EXPORT void	vl_gmm_set_initialization (VlGMM *self, VlGMMInitialization init)
	Set initialization algorithm.
VL_EXPORT void	vl_gmm_set_kmeans_init_object (VlGMM self, VlKMeans kmeans)
	Set KMeans initialization object.
VL_EXPORT void	vl_gmm_set_covariance_lower_bounds (VlGMM self, double const bounds)
	Set the lower bounds on diagonal covariance values.
VL_EXPORT void	vl_gmm_set_covariance_lower_bound (VlGMM *self, double bound)
	Set the lower bounds on diagonal covariance values.
Get parameters
VL_EXPORT void const *	vl_gmm_get_means (VlGMM const *self)
	Get means.
VL_EXPORT void const *	vl_gmm_get_covariances (VlGMM const *self)
	Get covariances.
VL_EXPORT void const *	vl_gmm_get_priors (VlGMM const *self)
	Get priors.
VL_EXPORT void const *	vl_gmm_get_posteriors (VlGMM const *self)
	Get posteriors.
VL_EXPORT vl_type	vl_gmm_get_data_type (VlGMM const *self)
	Get data type.
VL_EXPORT vl_size	vl_gmm_get_dimension (VlGMM const *self)
	Get data dimension.
VL_EXPORT vl_size	vl_gmm_get_num_repetitions (VlGMM const *self)
	Get maximum number of repetitions.
VL_EXPORT vl_size	vl_gmm_get_num_data (VlGMM const *self)
	Get the number of data points.
VL_EXPORT vl_size	vl_gmm_get_num_clusters (VlGMM const *self)
	Get the number of clusters.
VL_EXPORT double	vl_gmm_get_loglikelihood (VlGMM const *self)
	Get the log likelihood of the current mixture.
VL_EXPORT int	vl_gmm_get_verbosity (VlGMM const *self)
	Get verbosity level.
VL_EXPORT vl_size	vl_gmm_get_max_num_iterations (VlGMM const *self)
	Get maximum number of iterations.
VL_EXPORT VlGMMInitialization	vl_gmm_get_initialization (VlGMM const *self)
	Get initialization algorithm.
VL_EXPORT VlKMeans *	vl_gmm_get_kmeans_init_object (VlGMM const *self)
	Get KMeans initialization object.
VL_EXPORT double const *	vl_gmm_get_covariance_lower_bounds (VlGMM const *self)
	Get the lower bound on the diagonal covariance values.

Detailed Description

GMM (Gaussian Mixture Models (GMM))

Author:: David Novotny; Andrea Vedaldi

Definition in file gmm.h.

Typedef Documentation

typedef struct _VlGMM VlGMM

Definition at line 31 of file gmm.h.

typedef enum _VlGMMInitialization VlGMMInitialization

GMM initialization algorithms.

Enumeration Type Documentation

enum _VlGMMInitialization

GMM initialization algorithms.

Enumerator:

VlGMMKMeans	Initialize GMM from KMeans clustering.
VlGMMRand	Initialize GMM parameters by selecting points at random.
VlGMMCustom	User specifies the initial GMM parameters.

Definition at line 21 of file gmm.h.

Function Documentation

VL_EXPORT double vl_get_gmm_data_posteriors_d	(	double *	posteriors,
		vl_size	numClusters,
		vl_size	numData,
		double const *	priors,
		double const *	means,
		vl_size	dimension,
		double const *	covariances,
		double const *	data
	)

VL_EXPORT double vl_get_gmm_data_posteriors_f	(	float *	posteriors,
		vl_size	numClusters,
		vl_size	numData,
		float const *	priors,
		float const *	means,
		vl_size	dimension,
		float const *	covariances,
		float const *	data
	)

VL_EXPORT double vl_gmm_cluster	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

VL_EXPORT void vl_gmm_delete ( VlGMM * self )

Deletes a GMM object.

Parameters:

self	GMM object instance.

The function deletes the GMM object instance created by vl_gmm_new.

Definition at line 414 of file gmm.c.

VL_EXPORT double vl_gmm_em	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

VL_EXPORT double const* vl_gmm_get_covariance_lower_bounds ( VlGMM const * self )

Get the lower bound on the diagonal covariance values.

Parameters:

self object

Returns:: lower bound on covariances.

Definition at line 644 of file gmm.c.

VL_EXPORT void const* vl_gmm_get_covariances ( VlGMM const * self )

Get covariances.

Parameters:

self object

Returns:: diagonals of cluster covariance matrices.

Definition at line 513 of file gmm.c.

VL_EXPORT vl_type vl_gmm_get_data_type ( VlGMM const * self )

Get data type.

Parameters:

self object

Returns:: data type.

Definition at line 436 of file gmm.c.

VL_EXPORT vl_size vl_gmm_get_dimension ( VlGMM const * self )

Get data dimension.

Parameters:

self object

Returns:: data dimension.

Definition at line 592 of file gmm.c.

VL_EXPORT VlGMMInitialization vl_gmm_get_initialization ( VlGMM const * self )

Get initialization algorithm.

Parameters:

self object

Returns:: initialization algorithm.

Definition at line 603 of file gmm.c.

VL_EXPORT VlKMeans* vl_gmm_get_kmeans_init_object ( VlGMM const * self )

Get KMeans initialization object.

Parameters:

self object

Returns:: kmeans initialization object.

Definition at line 622 of file gmm.c.

VL_EXPORT double vl_gmm_get_loglikelihood ( VlGMM const * self )

Get the log likelihood of the current mixture.

Parameters:

self object

Returns:: loglikelihood.

Definition at line 469 of file gmm.c.

VL_EXPORT vl_size vl_gmm_get_max_num_iterations ( VlGMM const * self )

Get maximum number of iterations.

Parameters:

self object

Returns:: maximum number of iterations.

Definition at line 546 of file gmm.c.

VL_EXPORT void const* vl_gmm_get_means ( VlGMM const * self )

Get means.

Parameters:

self object

Returns:: cluster means.

Definition at line 502 of file gmm.c.

VL_EXPORT vl_size vl_gmm_get_num_clusters ( VlGMM const * self )

Get the number of clusters.

Parameters:

self object

Returns:: number of clusters.

Definition at line 447 of file gmm.c.

VL_EXPORT vl_size vl_gmm_get_num_data ( VlGMM const * self )

Get the number of data points.

Parameters:

self object

Returns:: number of data points.

Definition at line 458 of file gmm.c.

VL_EXPORT vl_size vl_gmm_get_num_repetitions ( VlGMM const * self )

Get maximum number of repetitions.

Parameters:

self object

Returns:: current number of repretitions for quantization.

Definition at line 568 of file gmm.c.

VL_EXPORT void const* vl_gmm_get_posteriors ( VlGMM const * self )

Get posteriors.

Parameters:

self object

Returns:: posterior probabilities of cluster memberships.

Definition at line 535 of file gmm.c.

VL_EXPORT void const* vl_gmm_get_priors ( VlGMM const * self )

Get priors.

Parameters:

self object

Returns:: priors of cluster gaussians.

Definition at line 524 of file gmm.c.

VL_EXPORT int vl_gmm_get_verbosity ( VlGMM const * self )

Get verbosity level.

Parameters:

self object

Returns:: verbosity level.

Definition at line 480 of file gmm.c.

VL_EXPORT void vl_gmm_init_with_kmeans	(	VlGMM *	self,
		void const *	data,
		vl_size	numData,
		VlKMeans *	kmeansInit
	)

VL_EXPORT void vl_gmm_init_with_rand_data	(	VlGMM *	self,
		void const *	data,
		vl_size	numData
	)

VL_EXPORT VlGMM* vl_gmm_new	(	vl_type	dataType,
		vl_size	dimension,
		vl_size	numComponents
	)

Create a new GMM object.

Parameters:

dataType	type of data (VL_TYPE_FLOAT or VL_TYPE_DOUBLE)
dimension	dimension of the data.
numComponents	number of Gaussian mixture components.

Returns:: new GMM object instance.

Definition at line 354 of file gmm.c.

VL_EXPORT VlGMM* vl_gmm_new_copy ( VlGMM const * gmm )

VL_EXPORT void vl_gmm_reset ( VlGMM * self )

Reset state.

Parameters:

self object.

The function reset the state of the GMM object. It deletes any stored posterior and other internal state variables.

Definition at line 392 of file gmm.c.

VL_EXPORT void vl_gmm_set_covariance_lower_bound	(	VlGMM *	self,
		double	bound
	)

Set the lower bounds on diagonal covariance values.

Parameters:

self	object.
bound	bound.

While there is one lower bound per dimension, this function sets all of them to the specified scalar. Use vl_gmm_set_covariance_lower_bounds to set them individually.

Definition at line 669 of file gmm.c.

VL_EXPORT void vl_gmm_set_covariance_lower_bounds	(	VlGMM *	self,
		double const *	bounds
	)

Set the lower bounds on diagonal covariance values.

Parameters:

self	object.
bounds	bounds.

There is one lower bound per dimension. Use vl_gmm_set_covariance_lower_bound to set all of them to a given scalar.

Definition at line 656 of file gmm.c.

VL_EXPORT void vl_gmm_set_covariances	(	VlGMM *	self,
		void const *	covariances
	)

VL_EXPORT void vl_gmm_set_initialization	(	VlGMM *	self,
		VlGMMInitialization	init
	)

Set initialization algorithm.

Parameters:

self	object
init	initialization algorithm.

Definition at line 613 of file gmm.c.

VL_EXPORT void vl_gmm_set_kmeans_init_object	(	VlGMM *	self,
		VlKMeans *	kmeans
	)

Set KMeans initialization object.

Parameters:

self	object
kmeans	initialization KMeans object.

Definition at line 631 of file gmm.c.

VL_EXPORT void vl_gmm_set_max_num_iterations	(	VlGMM *	self,
		vl_size	maxNumIterations
	)

Set maximum number of iterations.

Parameters:

self	VlGMM filter.
maxNumIterations	maximum number of iterations.

Definition at line 557 of file gmm.c.

VL_EXPORT void vl_gmm_set_means	(	VlGMM *	self,
		void const *	means
	)

VL_EXPORT void vl_gmm_set_num_repetitions	(	VlGMM *	self,
		vl_size	numRepetitions
	)

Set maximum number of repetitions.

Parameters:

self	object
numRepetitions	maximum number of repetitions. The number of repetitions cannot be smaller than 1.

Definition at line 580 of file gmm.c.

VL_EXPORT void vl_gmm_set_priors	(	VlGMM *	self,
		void const *	priors
	)

VL_EXPORT void vl_gmm_set_verbosity	(	VlGMM *	self,
		int	verbosity
	)

Set verbosity level.

Parameters:

self	object
verbosity	verbosity level.

Definition at line 491 of file gmm.c.

Typedefs

Enumerations

Functions

Detailed Description

Typedef Documentation

Enumeration Type Documentation

Function Documentation