Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Unscented Kalman filter. More...

#include <opencv2/tracking/kalman_filters.hpp>

Inheritance diagram for cv::tracking::AugmentedUnscentedKalmanFilterParams:

Public Member Functions
	AugmentedUnscentedKalmanFilterParams ()

	AugmentedUnscentedKalmanFilterParams (int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)

void	init (int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)

Public Member Functions inherited from cv::tracking::UnscentedKalmanFilterParams
	UnscentedKalmanFilterParams ()

	UnscentedKalmanFilterParams (int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)

void	init (int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)

Additional Inherited Members
Public Attributes inherited from cv::tracking::UnscentedKalmanFilterParams
double	alpha
	Default is 1e-3. More...

double	beta
	Default is 2.0. More...

int	CP
	Dimensionality of the control vector. More...

int	dataType
	Type of elements of vectors and matrices, default is CV_64F. More...

int	DP
	Dimensionality of the state vector. More...

Mat	errorCovInit
	State estimate cross-covariance matrix, DP x DP, default is identity. More...

double	k
	Default is 0. More...

Mat	measurementNoiseCov
	Measurement noise cross-covariance matrix, MP x MP. More...

Ptr< UkfSystemModel >	model
	Object of the class containing functions for computing the next state and the measurement. More...

int	MP
	Dimensionality of the measurement vector. More...

Mat	processNoiseCov
	Process noise cross-covariance matrix, DP x DP. More...

Mat	stateInit
	Initial state, DP x 1, default is zero. More...

Detailed Description

Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Unscented Kalman filter.

Constructor & Destructor Documentation

cv::tracking::AugmentedUnscentedKalmanFilterParams::AugmentedUnscentedKalmanFilterParams ( )

inline

cv::tracking::AugmentedUnscentedKalmanFilterParams::AugmentedUnscentedKalmanFilterParams	(	int	dp,
		int	mp,
		int	cp,
		double	processNoiseCovDiag,
		double	measurementNoiseCovDiag,
		Ptr< UkfSystemModel >	dynamicalSystem,
		int	type = `CV_64F`
	)

Parameters

dp	- dimensionality of the state vector,
mp	- dimensionality of the measurement vector,
cp	- dimensionality of the control vector,
processNoiseCovDiag	- value of elements on main diagonal process noise cross-covariance matrix,
measurementNoiseCovDiag	- value of elements on main diagonal measurement noise cross-covariance matrix,
dynamicalSystem	- ptr to object of the class containing functions for computing the next state and the measurement,
type	- type of the created matrices that should be CV_32F or CV_64F.

void cv::tracking::AugmentedUnscentedKalmanFilterParams::init	(	int	dp,
		int	mp,
		int	cp,
		double	processNoiseCovDiag,
		double	measurementNoiseCovDiag,
		Ptr< UkfSystemModel >	dynamicalSystem,
		int	type = `CV_64F`
	)

The function for initialization of Augmented Unscented Kalman filter

Parameters

dp	- dimensionality of the state vector,
mp	- dimensionality of the measurement vector,
cp	- dimensionality of the control vector,
processNoiseCovDiag	- value of elements on main diagonal process noise cross-covariance matrix,
measurementNoiseCovDiag	- value of elements on main diagonal measurement noise cross-covariance matrix,
dynamicalSystem	- object of the class containing functions for computing the next state and the measurement,
type	- type of the created matrices that should be CV_32F or CV_64F.

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