C# 클래스 Emgu.CV.Kalman

Kalman Filter
상속: DisposableObject
파일 보기 프로젝트 열기: fajoy/RTSPExample 1 사용 예제들

공개 메소드들

메소드 설명
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

보호된 메소드들

메소드 설명
DisposeObject ( ) : void

Release unmanaged resource

ReleaseManagedResources ( ) : void

Release all the matrix associated to this object

메소드 상세

Correct() 공개 메소드

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
리턴 Matrix

DisposeObject() 보호된 메소드

Release unmanaged resource
protected DisposeObject ( ) : void
리턴 void

Kalman() 공개 메소드

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)
리턴 System

Kalman() 공개 메소드

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)
리턴 System

Kalman() 공개 메소드

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
리턴 System

Predict() 공개 메소드

Estimates the subsequent stochastic model state by its current state
public Predict ( ) : Matrix
리턴 Matrix

Predict() 공개 메소드

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
리턴 Matrix

ReleaseManagedResources() 보호된 메소드

Release all the matrix associated to this object
protected ReleaseManagedResources ( ) : void
리턴 void