@Namespace(value="cv::tracking") @NoOffset @Properties(inherit=opencv_tracking.class) public class UnscentedKalmanFilterParams extends Pointer
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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UnscentedKalmanFilterParams()
The constructors.
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UnscentedKalmanFilterParams(int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
UkfSystemModel dynamicalSystem) |
UnscentedKalmanFilterParams(int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
UkfSystemModel dynamicalSystem,
int type) |
UnscentedKalmanFilterParams(long size)
Native array allocator.
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UnscentedKalmanFilterParams(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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double |
alpha()
Default is 1e-3.
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UnscentedKalmanFilterParams |
alpha(double setter) |
double |
beta()
Default is 2.0.
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UnscentedKalmanFilterParams |
beta(double setter) |
int |
CP()
Dimensionality of the control vector.
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UnscentedKalmanFilterParams |
CP(int setter) |
int |
dataType()
Type of elements of vectors and matrices, default is CV_64F.
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UnscentedKalmanFilterParams |
dataType(int setter) |
int |
DP()
Dimensionality of the state vector.
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UnscentedKalmanFilterParams |
DP(int setter) |
Mat |
errorCovInit()
State estimate cross-covariance matrix, DP x DP, default is identity.
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UnscentedKalmanFilterParams |
errorCovInit(Mat setter) |
void |
init(int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
UkfSystemModel dynamicalSystem) |
void |
init(int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
UkfSystemModel dynamicalSystem,
int type)
The function for initialization of Unscented Kalman filter
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double |
k()
Default is 0.
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UnscentedKalmanFilterParams |
k(double setter) |
Mat |
measurementNoiseCov()
Measurement noise cross-covariance matrix, MP x MP.
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UnscentedKalmanFilterParams |
measurementNoiseCov(Mat setter) |
UkfSystemModel |
model()
Object of the class containing functions for computing the next state and the measurement.
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UnscentedKalmanFilterParams |
model(UkfSystemModel setter) |
int |
MP()
Dimensionality of the measurement vector.
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UnscentedKalmanFilterParams |
MP(int setter) |
UnscentedKalmanFilterParams |
position(long position) |
Mat |
processNoiseCov()
Process noise cross-covariance matrix, DP x DP.
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UnscentedKalmanFilterParams |
processNoiseCov(Mat setter) |
Mat |
stateInit()
Initial state, DP x 1, default is zero.
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UnscentedKalmanFilterParams |
stateInit(Mat setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero
public UnscentedKalmanFilterParams(Pointer p)
Pointer.Pointer(Pointer)
.public UnscentedKalmanFilterParams(long size)
Pointer.position(long)
.public UnscentedKalmanFilterParams()
public UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, @opencv_core.Ptr UkfSystemModel dynamicalSystem, int type)
dp
- - dimensionality of the state vector,mp
- - dimensionality of the measurement vector,cp
- - dimensionality of the control vector,processNoiseCovDiag
- - value of elements on main diagonal process noise cross-covariance matrix,measurementNoiseCovDiag
- - value of elements on main diagonal measurement noise cross-covariance matrix,dynamicalSystem
- - ptr to object of the class containing functions for computing the next state and the measurement,type
- - type of the created matrices that should be CV_32F or CV_64F.public UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, @opencv_core.Ptr UkfSystemModel dynamicalSystem)
public UnscentedKalmanFilterParams position(long position)
public int DP()
public UnscentedKalmanFilterParams DP(int setter)
public int MP()
public UnscentedKalmanFilterParams MP(int setter)
public int CP()
public UnscentedKalmanFilterParams CP(int setter)
public int dataType()
public UnscentedKalmanFilterParams dataType(int setter)
public UnscentedKalmanFilterParams stateInit(Mat setter)
@ByRef public Mat errorCovInit()
public UnscentedKalmanFilterParams errorCovInit(Mat setter)
public UnscentedKalmanFilterParams processNoiseCov(Mat setter)
@ByRef public Mat measurementNoiseCov()
public UnscentedKalmanFilterParams measurementNoiseCov(Mat setter)
public double alpha()
public UnscentedKalmanFilterParams alpha(double setter)
public double k()
public UnscentedKalmanFilterParams k(double setter)
public double beta()
public UnscentedKalmanFilterParams beta(double setter)
@opencv_core.Ptr public UkfSystemModel model()
public UnscentedKalmanFilterParams model(UkfSystemModel setter)
public void init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, @opencv_core.Ptr UkfSystemModel dynamicalSystem, int type)
dp
- - dimensionality of the state vector,mp
- - dimensionality of the measurement vector,cp
- - dimensionality of the control vector,processNoiseCovDiag
- - value of elements on main diagonal process noise cross-covariance matrix,measurementNoiseCovDiag
- - value of elements on main diagonal measurement noise cross-covariance matrix,dynamicalSystem
- - ptr to object of the class containing functions for computing the next state and the measurement,type
- - type of the created matrices that should be CV_32F or CV_64F.public void init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, @opencv_core.Ptr UkfSystemModel dynamicalSystem)
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