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)
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Field Summary
Fields Modifier and Type Field Description protected longnativeObj -
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)protectedKalmanFilter(long addr) -
Method Summary
Modifier and Type Method Description static KalmanFilter__fromPtr__(long addr)Matcorrect(Mat measurement)Updates the predicted state from the measurement.protected voidfinalize()Matget_controlMatrix()Matget_errorCovPost()Matget_errorCovPre()Matget_gain()Matget_measurementMatrix()Matget_measurementNoiseCov()Matget_processNoiseCov()Matget_statePost()Matget_statePre()Matget_transitionMatrix()longgetNativeObjAddr()Matpredict()Computes a predicted state.Matpredict(Mat control)Computes a predicted state.voidset_controlMatrix(Mat controlMatrix)voidset_errorCovPost(Mat errorCovPost)voidset_errorCovPre(Mat errorCovPre)voidset_gain(Mat gain)voidset_measurementMatrix(Mat measurementMatrix)voidset_measurementNoiseCov(Mat measurementNoiseCov)voidset_processNoiseCov(Mat processNoiseCov)voidset_statePost(Mat statePost)voidset_statePre(Mat statePre)voidset_transitionMatrix(Mat transitionMatrix)
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Field Details
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Constructor Details
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KalmanFilter
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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.
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KalmanFilter
- Parameters:
dynamParams- Dimensionality of the state.measureParams- Dimensionality of the measurement.controlParams- Dimensionality of the control vector.
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KalmanFilter
- Parameters:
dynamParams- Dimensionality of the state.measureParams- Dimensionality of the measurement.
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Method Details
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getNativeObjAddr
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__fromPtr__
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predict
Computes a predicted state.- Parameters:
control- The optional input control- Returns:
- automatically generated
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predict
Computes a predicted state.- Returns:
- automatically generated
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correct
Updates the predicted state from the measurement.- Parameters:
measurement- The measured system parameters- Returns:
- automatically generated
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get_statePre
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set_statePre
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get_statePost
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set_statePost
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get_transitionMatrix
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set_transitionMatrix
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get_controlMatrix
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set_controlMatrix
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get_measurementMatrix
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set_measurementMatrix
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get_processNoiseCov
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set_processNoiseCov
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get_measurementNoiseCov
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set_measurementNoiseCov
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get_errorCovPre
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set_errorCovPre
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get_gain
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set_gain
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get_errorCovPost
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set_errorCovPost
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finalize
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