C# Class Emgu.CV.Kalman

Kalman Filter

Inheritance: DisposableObject

Méthodes publiques

Méthode	Description
Correct ( Matrix measurement ) : Matrix	Adjusts stochastic model state on the basis of the given measurement of the model state The function stores adjusted state at kalman->state_post and returns it on output
Kalman ( Matrix initialState, Matrix transitionMatrix, Matrix measurementMatrix, Matrix processNoiseCovarianceMatrix, Matrix measurementNoiseCovarianceMatrix ) : System	Create a Kalman Filter using the specific values
Kalman ( Matrix initialState, Matrix transitionMatrix, Matrix controlMatrix, Matrix measurementMatrix, Matrix processNoiseCovarianceMatrix, Matrix measurementNoiseCovarianceMatrix ) : System	Create a Kalman Filter using the specific values
Kalman ( int dynamParams, int measureParams, int controlParams ) : System	Allocates CvKalman and all its matrices and initializes them somehow.
Predict ( ) : Matrix	Estimates the subsequent stochastic model state by its current state
Predict ( Matrix control ) : Matrix	Estimates the subsequent stochastic model state by its current state and stores it at PredictedState

Méthode	Description
DisposeObject ( ) : void	Release unmanaged resource
ReleaseManagedResources ( ) : void	Release all the matrix associated to this object

Adjusts stochastic model state on the basis of the given measurement of the model state

The function stores adjusted state at kalman->state_post and returns it on output

public Correct ( Matrix measurement ) : Matrix
measurement	Matrix	The measurement data
Résultat	Matrix

Release unmanaged resource

protected DisposeObject ( ) : void
Résultat	void

Create a Kalman Filter using the specific values

public Kalman ( Matrix initialState, Matrix transitionMatrix, Matrix measurementMatrix, Matrix processNoiseCovarianceMatrix, Matrix measurementNoiseCovarianceMatrix ) : System
initialState	Matrix	The m x 1 matrix
transitionMatrix	Matrix	The m x m matrix (A)
measurementMatrix	Matrix	The n x m matrix (H)
processNoiseCovarianceMatrix	Matrix	The n x n matrix (Q)
measurementNoiseCovarianceMatrix	Matrix	The m x m matrix (R)
Résultat	System

Create a Kalman Filter using the specific values

public Kalman ( Matrix initialState, Matrix transitionMatrix, Matrix controlMatrix, Matrix measurementMatrix, Matrix processNoiseCovarianceMatrix, Matrix measurementNoiseCovarianceMatrix ) : System
initialState	Matrix	The m x 1 matrix
transitionMatrix	Matrix	The m x m matrix (A)
controlMatrix	Matrix	The m x n matrix (B)
measurementMatrix	Matrix	The n x m matrix (H)
processNoiseCovarianceMatrix	Matrix	The n x n matrix (Q)
measurementNoiseCovarianceMatrix	Matrix	The m x m matrix (R)
Résultat	System

Allocates CvKalman and all its matrices and initializes them somehow.

public Kalman ( int dynamParams, int measureParams, int controlParams ) : System
dynamParams	int	dimensionality of the state vector
measureParams	int	dimensionality of the measurement vector
controlParams	int	dimensionality of the control vector
Résultat	System

Estimates the subsequent stochastic model state by its current state

public Predict ( ) : Matrix
Résultat	Matrix

Estimates the subsequent stochastic model state by its current state and stores it at PredictedState

public Predict ( Matrix control ) : Matrix
control	Matrix	the control vector
Résultat	Matrix

Release all the matrix associated to this object

protected ReleaseManagedResources ( ) : void
Résultat	void