FD::GMM Class Reference

#include <gmm.h>

Inheritance diagram for FD::GMM:

[legend]Collaboration diagram for FD::GMM:

[legend]List of all members.

Public Types
enum	GMM_Mode { real, accum }
Public Member Functions
	GMM (int nb_gauss, int dim, Covariance *(*cov_new)(int))
	nb_gaussians (0)
	mode (accum)
	nb_frames_aligned (0)
	dimensions (1)
	using_gaussianIDs (false)
void	save (std::string file)
int	get_nb_gaussians () const
Gaussian &	gaussian (int i) const
void	accum_to_gaussian (int i, const float *fr)
void	init (std::vector< float * > frames)
void	kmeans1 (std::vector< float * > frames, int nb_iterations=1)
void	split1 ()
void	kmeans2 (std::vector< float * > frames, GMM *gmm)
void	adaptMAP (std::vector< float * > frame, GMM *gmm)
void	to_real ()
void	reset_to_accum_mode ()
Score	minDistance (float *fr, Covariance *cov) const
Score	score (float *fr) const
void	binary_split ()
std::vector< Score >	minDistance (std::vector< float * > fr) const
std::vector< Score >	score (std::vector< float * > fr) const
void	toIDsUsing (GaussianSet &gauss)
void	toPtrsUsing (const GaussianSet &gauss)
DiagGMM *	createDiagGMM ()
virtual void	printOn (std::ostream &out=std::cout) const
void	readFrom (std::istream &in=std::cin)
Public Attributes
	__pad0__: gaussians(std::vector<RCPtr<Gaussian> >())
Protected Attributes
std::vector< RCPtr< Gaussian > >	gaussians
std::vector< float >	apriori
int	nb_gaussians
int	mode
int	nb_frames_aligned
int	dimensions
bool	using_gaussianIDs
std::vector< int >	gaussianIDs
Friends
std::istream &	operator>> (std::istream &in, GMM &gmm)

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Detailed Description

Gaussian Mixture Model (GMM) class

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Constructor & Destructor Documentation

FD::GMM::GMM (  int  nb_gauss, int  dim, Covariance *(*)(int)  cov_new )  [inline]

Construct a GMM with nb_gauss gaussians, dim dimensions and a covariance pseudo-factory

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Member Function Documentation

void FD::GMM::accum_to_gaussian (  int  i, const float *  fr )  [inline]

Accumulates (adds) the frame to the i'th gaussian

void FD::GMM::adaptMAP (  std::vector< float * >  frame, GMM *  gmm )

Perform MAP adaptation (using another GMM to score)

void FD::GMM::binary_split (   )

Double the number of gaussians

DiagGMM* FD::GMM::createDiagGMM (   )

Creates a DiagGMM object from a GMM

Gaussian& FD::GMM::gaussian (  int  i  )  const [inline]

Returns the i'th gaussian

int FD::GMM::get_nb_gaussians (   )  const [inline]

Returns the number of gaussians in the GMM

void FD::GMM::init (  std::vector< float * >  frames  )

Randomly init the GMM with a list (STL vector) of frames

void FD::GMM::kmeans1 (  std::vector< float * >  frames, int  nb_iterations = 1 )

Performs k-means training

void FD::GMM::kmeans2 (  std::vector< float * >  frames, GMM *  gmm )

Performs k-means training (using another GMM to score)

std::vector<Score> FD::GMM::minDistance (  std::vector< float * >  fr  )  const

Score a list (STL vector) of frames against the GMM without using the covariances (nearest euclidian distance)

Score FD::GMM::minDistance (  float *  fr, Covariance *  cov )  const

Score a frame against the GMM without using the covariances (nearest euclidian distance)

virtual void FD::GMM::printOn (  std::ostream &  out = std::cout  )  const [virtual]

print function used for operator << Implements FD::Object.

void FD::GMM::readFrom (  std::istream &  in = std::cin  )  [virtual]

Read function used for operator >> Reimplemented from FD::Object.

void FD::GMM::reset_to_accum_mode (   )

Converts the GMM from real mode to accum mode and set everything to zero

std::vector<Score> FD::GMM::score (  std::vector< float * >  fr  )  const

Score a list (STL vector) of frames against the GMM

Score FD::GMM::score (  float *  fr  )  const

Score a frame against the GMM

void FD::GMM::split1 (   )

splits the largest gaussian in two

void FD::GMM::to_real (   )

Converts the GMM from accum mode to real mode

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Friends And Related Function Documentation

std::istream& operator>> (  std::istream &  in, GMM &  gmm )  [friend]

extractor for GMM

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Member Data Documentation

std::vector<float> FD::GMM::apriori [protected]

STL vector containing all the apriori weights of the gaussians

int FD::GMM::dimensions [protected]

Number of dimensions

std::vector<int> FD::GMM::gaussianIDs [protected]

STL vector containing all the gaussian IDs in the GMM

std::vector<RCPtr<Gaussian> > FD::GMM::gaussians [protected]

STL vector containing all the gaussians in the GMM

int FD::GMM::mode [protected]

Whether of not the GMM trained (like real/accum mode) (GMM_Mode)

int FD::GMM::nb_frames_aligned [protected]

Number of frames aligned to (used to train) the GMM

int FD::GMM::nb_gaussians [protected]

Number of gaussians in the GMM

bool FD::GMM::using_gaussianIDs [protected]

Was the gaussian loaded using indexes for mean

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

• gmm.h

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