org.opencv.video
public class KalmanFilter extends java.lang.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:
Constructor and Description |
---|
KalmanFilter()
The constructors.
|
KalmanFilter(int dynamParams,
int measureParams)
The constructors.
|
KalmanFilter(int dynamParams,
int measureParams,
int controlParams,
int type)
The constructors.
|
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)
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 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 Mat correct(Mat measurement)
Updates the predicted state from the measurement.
measurement
- The measured system parameterspublic Mat predict()
Computes a predicted state.
public Mat predict(Mat control)
Computes a predicted state.
control
- The optional input control