@Namespace(value="cv") @NoOffset @Properties(inherit=opencv_video.class) public class KalmanFilter extends Pointer
The class implements a standard Kalman filter
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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KalmanFilter() |
KalmanFilter(int dynamParams,
int measureParams) |
KalmanFilter(int dynamParams,
int measureParams,
int controlParams,
int type)
\overload
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KalmanFilter(long size)
Native array allocator.
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KalmanFilter(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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Mat |
controlMatrix()
control matrix (B) (not used if there is no control)
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KalmanFilter |
controlMatrix(Mat setter) |
Mat |
correct(Mat measurement)
\brief Updates the predicted state from the measurement.
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Mat |
errorCovPost()
posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P'(k)
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KalmanFilter |
errorCovPost(Mat setter) |
Mat |
errorCovPre()
priori error estimate covariance matrix (P'(k)): P'(k)=A*P(k-1)*At + Q)
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KalmanFilter |
errorCovPre(Mat setter) |
Mat |
gain()
Kalman gain matrix (K(k)): K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R)
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KalmanFilter |
gain(Mat setter) |
KalmanFilter |
getPointer(long i) |
void |
init(int dynamParams,
int measureParams) |
void |
init(int dynamParams,
int measureParams,
int controlParams,
int type)
\brief Re-initializes Kalman filter.
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Mat |
measurementMatrix()
measurement matrix (H)
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KalmanFilter |
measurementMatrix(Mat setter) |
Mat |
measurementNoiseCov()
measurement noise covariance matrix (R)
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KalmanFilter |
measurementNoiseCov(Mat setter) |
KalmanFilter |
position(long position) |
Mat |
predict() |
Mat |
predict(Mat control)
\brief Computes a predicted state.
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Mat |
processNoiseCov()
process noise covariance matrix (Q)
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KalmanFilter |
processNoiseCov(Mat setter) |
Mat |
statePost()
corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k))
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KalmanFilter |
statePost(Mat setter) |
Mat |
statePre()
predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k)
|
KalmanFilter |
statePre(Mat setter) |
Mat |
temp1() |
KalmanFilter |
temp1(Mat setter) |
Mat |
temp2() |
KalmanFilter |
temp2(Mat setter) |
Mat |
temp3() |
KalmanFilter |
temp3(Mat setter) |
Mat |
temp4() |
KalmanFilter |
temp4(Mat setter) |
Mat |
temp5() |
KalmanFilter |
temp5(Mat setter) |
Mat |
transitionMatrix()
state transition matrix (A)
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KalmanFilter |
transitionMatrix(Mat setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public KalmanFilter(Pointer p)
Pointer(Pointer)
.public KalmanFilter(long size)
Pointer.position(long)
.public KalmanFilter()
public KalmanFilter(int dynamParams, int measureParams, int controlParams, int type)
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)
public KalmanFilter position(long position)
public KalmanFilter getPointer(long i)
getPointer
in class Pointer
public void init(int dynamParams, int measureParams, int controlParams, int type)
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 void init(int dynamParams, int measureParams)
@Const @ByRef public Mat predict(@Const @ByRef(nullValue="cv::Mat()") Mat control)
control
- The optional input control@Const @ByRef public Mat correct(@Const @ByRef Mat measurement)
measurement
- The measured system parameterspublic KalmanFilter statePre(Mat setter)
public KalmanFilter statePost(Mat setter)
public KalmanFilter transitionMatrix(Mat setter)
@ByRef public Mat controlMatrix()
public KalmanFilter controlMatrix(Mat setter)
public KalmanFilter measurementMatrix(Mat setter)
public KalmanFilter processNoiseCov(Mat setter)
public KalmanFilter measurementNoiseCov(Mat setter)
@ByRef public Mat errorCovPre()
public KalmanFilter errorCovPre(Mat setter)
public KalmanFilter gain(Mat setter)
@ByRef public Mat errorCovPost()
public KalmanFilter errorCovPost(Mat setter)
public KalmanFilter temp1(Mat setter)
public KalmanFilter temp2(Mat setter)
public KalmanFilter temp3(Mat setter)
public KalmanFilter temp4(Mat setter)
public KalmanFilter temp5(Mat setter)
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