KalmanFilterAsync extension
KalmanFilter implements a standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter. However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get an extended Kalman filter functionality.
For further details, please see: https://docs.opencv.org/4.6.0/dd/d6a/classcv_1_1KalmanFilter.html
- on
Methods
-
correctAsync(
Mat measurement) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getControlMatrix(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getErrorCovPost(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getErrorCovPre(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getGain(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getMeasurementMatrix(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getMeasurementNoiseCov(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getProcessNoiseCov(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getStatePost(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getStatePre(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTemp1(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTemp2(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTemp3(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTemp4(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTemp5(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
getTransitionMatrix(
) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
initAsync(
int dynamParams, int measureParams, {int controlParams = 0, int type = MatType.CV_32F}) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
predictAsync(
{Mat? control}) → Future< Mat> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setControlMatrix(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setErrorCovPost(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setErrorCovPre(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setGain(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setMeasurementMatrix(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setMeasurementNoiseCov(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setProcessNoiseCov(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setStatePost(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setStatePre(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
-
setTransitionMatrix(
Mat m) → Future< void> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension
Static Methods
-
createAsync(
int dynamParams, int measureParams, {int controlParams = 0, int type = MatType.CV_32F}) → Future< KalmanFilter> -
Available on KalmanFilter, provided by the KalmanFilterAsync extension