public class KalmanFilter extends Object
Kalman filter class.
The class implements a standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter,
[Welch95]. However, you can modify transitionMatrix,
controlMatrix, and measurementMatrix to get an
extended Kalman filter functionality. See the OpenCV sample kalman.cpp.
Note:
| Modifier and Type | Field and Description |
|---|---|
protected long |
nativeObj |
| Modifier | Constructor and Description |
|---|---|
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KalmanFilter()
The constructors.
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|
KalmanFilter(int dynamParams,
int measureParams)
The constructors.
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KalmanFilter(int dynamParams,
int measureParams,
int controlParams,
int type)
The constructors.
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protected |
KalmanFilter(long addr) |
| Modifier and Type | Method and Description |
|---|---|
Mat |
correct(Mat measurement)
Updates the predicted state from the measurement.
|
protected void |
finalize() |
Mat |
predict()
Computes a predicted state.
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Mat |
predict(Mat control)
Computes a predicted state.
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protected KalmanFilter(long addr)
public KalmanFilter()
The constructors.
The full constructor.
Note: In C API when CvKalman* kalmanFilter structure is not
needed anymore, it should be released with cvReleaseKalman(&kalmanFilter)
public KalmanFilter(int dynamParams,
int measureParams,
int controlParams,
int type)
The constructors.
The full constructor.
Note: In C API when CvKalman* kalmanFilter structure is not
needed anymore, it should be released with cvReleaseKalman(&kalmanFilter)
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.public KalmanFilter(int dynamParams,
int measureParams)
The constructors.
The full constructor.
Note: In C API when CvKalman* kalmanFilter structure is not
needed anymore, it should be released with cvReleaseKalman(&kalmanFilter)
dynamParams - Dimensionality of the state.measureParams - Dimensionality of the measurement.public Mat correct(Mat measurement)
Updates the predicted state from the measurement.
measurement - The measured system parameterspublic Mat predict(Mat control)
Computes a predicted state.
control - The optional input controlpublic Mat predict()
Computes a predicted state.
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