OpenCV  4.5.3 Open Source Computer Vision
cv::detail::tracking::kalman_filters::AugmentedUnscentedKalmanFilterParams Class Reference

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::detail::tracking::kalman_filters::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::detail::tracking::kalman_filters::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)

Public Attributes inherited from cv::detail::tracking::kalman_filters::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< UkfSystemModelmodel
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.

◆ AugmentedUnscentedKalmanFilterParams() [1/2]

 cv::detail::tracking::kalman_filters::AugmentedUnscentedKalmanFilterParams::AugmentedUnscentedKalmanFilterParams ( )
inline

◆ AugmentedUnscentedKalmanFilterParams() [2/2]

 cv::detail::tracking::kalman_filters::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.

◆ init()

 void cv::detail::tracking::kalman_filters::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: