Package org.opencv.video
Class KalmanFilter
java.lang.Object
org.opencv.video.KalmanFilter
public class KalmanFilter extends Object
Kalman filter class.
The class implements a standard Kalman filter <http://en.wikipedia.org/wiki/Kalman_filter>,
CITE: Welch95 . However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get
an extended Kalman filter functionality.
Note: In C API when CvKalman\* kalmanFilter structure is not needed anymore, it should be released
with cvReleaseKalman(&kalmanFilter)
-
Field Summary
Fields Modifier and Type Field Description protected long
nativeObj
-
Constructor Summary
Constructors Modifier Constructor Description KalmanFilter()
KalmanFilter(int dynamParams, int measureParams)
KalmanFilter(int dynamParams, int measureParams, int controlParams)
KalmanFilter(int dynamParams, int measureParams, int controlParams, int type)
protected
KalmanFilter(long addr)
-
Method Summary
Modifier and Type Method Description static KalmanFilter
__fromPtr__(long addr)
Mat
correct(Mat measurement)
Updates the predicted state from the measurement.protected void
finalize()
Mat
get_controlMatrix()
Mat
get_errorCovPost()
Mat
get_errorCovPre()
Mat
get_gain()
Mat
get_measurementMatrix()
Mat
get_measurementNoiseCov()
Mat
get_processNoiseCov()
Mat
get_statePost()
Mat
get_statePre()
Mat
get_transitionMatrix()
long
getNativeObjAddr()
Mat
predict()
Computes a predicted state.Mat
predict(Mat control)
Computes a predicted state.void
set_controlMatrix(Mat controlMatrix)
void
set_errorCovPost(Mat errorCovPost)
void
set_errorCovPre(Mat errorCovPre)
void
set_gain(Mat gain)
void
set_measurementMatrix(Mat measurementMatrix)
void
set_measurementNoiseCov(Mat measurementNoiseCov)
void
set_processNoiseCov(Mat processNoiseCov)
void
set_statePost(Mat statePost)
void
set_statePre(Mat statePre)
void
set_transitionMatrix(Mat transitionMatrix)
-
Field Details
-
Constructor Details
-
KalmanFilter
-
KalmanFilter
public KalmanFilter() -
KalmanFilter
- Parameters:
dynamParams
- Dimensionality of the state.measureParams
- Dimensionality of the measurement.controlParams
- Dimensionality of the control vector.type
- Type of the created matrices that should be CV_32F or CV_64F.
-
KalmanFilter
- Parameters:
dynamParams
- Dimensionality of the state.measureParams
- Dimensionality of the measurement.controlParams
- Dimensionality of the control vector.
-
KalmanFilter
- Parameters:
dynamParams
- Dimensionality of the state.measureParams
- Dimensionality of the measurement.
-
-
Method Details
-
getNativeObjAddr
-
__fromPtr__
-
predict
Computes a predicted state.- Parameters:
control
- The optional input control- Returns:
- automatically generated
-
predict
Computes a predicted state.- Returns:
- automatically generated
-
correct
Updates the predicted state from the measurement.- Parameters:
measurement
- The measured system parameters- Returns:
- automatically generated
-
get_statePre
-
set_statePre
-
get_statePost
-
set_statePost
-
get_transitionMatrix
-
set_transitionMatrix
-
get_controlMatrix
-
set_controlMatrix
-
get_measurementMatrix
-
set_measurementMatrix
-
get_processNoiseCov
-
set_processNoiseCov
-
get_measurementNoiseCov
-
set_measurementNoiseCov
-
get_errorCovPre
-
set_errorCovPre
-
get_gain
-
set_gain
-
get_errorCovPost
-
set_errorCovPost
-
finalize
-