org.bytedeco.javacpp

Class opencv_tracking.UnscentedKalmanFilterParams

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.opencv_tracking.UnscentedKalmanFilterParams

All Implemented Interfaces:

AutoCloseable

Direct Known Subclasses:

opencv_tracking.AugmentedUnscentedKalmanFilterParams

Enclosing class:

opencv_tracking

@Namespace(value="cv::tracking")
 @NoOffset
public static class opencv_tracking.UnscentedKalmanFilterParams
extends org.bytedeco.javacpp.Pointer

\brief Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.Pointer.CustomDeallocator, org.bytedeco.javacpp.Pointer.Deallocator, org.bytedeco.javacpp.Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
UnscentedKalmanFilterParams() The constructors.
UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, opencv_tracking.UkfSystemModel dynamicalSystem)
UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, opencv_tracking.UkfSystemModel dynamicalSystem, int type)
UnscentedKalmanFilterParams(long size) Native array allocator.
UnscentedKalmanFilterParams(org.bytedeco.javacpp.Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
double	alpha() Default is 1e-3.
opencv_tracking.UnscentedKalmanFilterParams	alpha(double alpha)
double	beta() Default is 2.0.
opencv_tracking.UnscentedKalmanFilterParams	beta(double beta)
int	CP() Dimensionality of the control vector.
opencv_tracking.UnscentedKalmanFilterParams	CP(int CP)
int	dataType() Type of elements of vectors and matrices, default is CV_64F.
opencv_tracking.UnscentedKalmanFilterParams	dataType(int dataType)
int	DP() Dimensionality of the state vector.
opencv_tracking.UnscentedKalmanFilterParams	DP(int DP)
opencv_core.Mat	errorCovInit() State estimate cross-covariance matrix, DP x DP, default is identity.
opencv_tracking.UnscentedKalmanFilterParams	errorCovInit(opencv_core.Mat errorCovInit)
void	init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, opencv_tracking.UkfSystemModel dynamicalSystem)
void	init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, opencv_tracking.UkfSystemModel dynamicalSystem, int type) The function for initialization of Unscented Kalman filter
double	k() Default is 0.
opencv_tracking.UnscentedKalmanFilterParams	k(double k)
opencv_core.Mat	measurementNoiseCov() Measurement noise cross-covariance matrix, MP x MP.
opencv_tracking.UnscentedKalmanFilterParams	measurementNoiseCov(opencv_core.Mat measurementNoiseCov)
opencv_tracking.UkfSystemModel	model() Object of the class containing functions for computing the next state and the measurement.
opencv_tracking.UnscentedKalmanFilterParams	model(opencv_tracking.UkfSystemModel model)
int	MP() Dimensionality of the measurement vector.
opencv_tracking.UnscentedKalmanFilterParams	MP(int MP)
opencv_tracking.UnscentedKalmanFilterParams	position(long position)
opencv_core.Mat	processNoiseCov() Process noise cross-covariance matrix, DP x DP.
opencv_tracking.UnscentedKalmanFilterParams	processNoiseCov(opencv_core.Mat processNoiseCov)
opencv_core.Mat	stateInit() Initial state, DP x 1, default is zero.
opencv_tracking.UnscentedKalmanFilterParams	stateInit(opencv_core.Mat stateInit)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams(org.bytedeco.javacpp.Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams(long size)

Native array allocator. Access with Pointer.position(long).

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams()

The constructors.

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams(int dp,
                                   int mp,
                                   int cp,
                                   double processNoiseCovDiag,
                                   double measurementNoiseCovDiag,
                                   @opencv_core.Ptr
                                   opencv_tracking.UkfSystemModel dynamicalSystem,
                                   int type)

Parameters:

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.

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams(int dp,
                                   int mp,
                                   int cp,
                                   double processNoiseCovDiag,
                                   double measurementNoiseCovDiag,
                                   @opencv_core.Ptr
                                   opencv_tracking.UkfSystemModel dynamicalSystem)

Method Detail

position

public opencv_tracking.UnscentedKalmanFilterParams position(long position)

Overrides:

position in class org.bytedeco.javacpp.Pointer

DP

public int DP()

Dimensionality of the state vector.

DP

public opencv_tracking.UnscentedKalmanFilterParams DP(int DP)

MP

public int MP()

Dimensionality of the measurement vector.

MP

public opencv_tracking.UnscentedKalmanFilterParams MP(int MP)

CP

public int CP()

Dimensionality of the control vector.

CP

public opencv_tracking.UnscentedKalmanFilterParams CP(int CP)

dataType

public int dataType()

Type of elements of vectors and matrices, default is CV_64F.

dataType

public opencv_tracking.UnscentedKalmanFilterParams dataType(int dataType)

stateInit

@ByRef
public opencv_core.Mat stateInit()

Initial state, DP x 1, default is zero.

stateInit

public opencv_tracking.UnscentedKalmanFilterParams stateInit(opencv_core.Mat stateInit)

errorCovInit

@ByRef
public opencv_core.Mat errorCovInit()

State estimate cross-covariance matrix, DP x DP, default is identity.

errorCovInit

public opencv_tracking.UnscentedKalmanFilterParams errorCovInit(opencv_core.Mat errorCovInit)

processNoiseCov

@ByRef
public opencv_core.Mat processNoiseCov()

Process noise cross-covariance matrix, DP x DP.

processNoiseCov

public opencv_tracking.UnscentedKalmanFilterParams processNoiseCov(opencv_core.Mat processNoiseCov)

measurementNoiseCov

@ByRef
public opencv_core.Mat measurementNoiseCov()

Measurement noise cross-covariance matrix, MP x MP.

measurementNoiseCov

public opencv_tracking.UnscentedKalmanFilterParams measurementNoiseCov(opencv_core.Mat measurementNoiseCov)

alpha

public double alpha()

Default is 1e-3.

alpha

public opencv_tracking.UnscentedKalmanFilterParams alpha(double alpha)

k

public double k()

Default is 0.

k

public opencv_tracking.UnscentedKalmanFilterParams k(double k)

beta

public double beta()

Default is 2.0.

beta

public opencv_tracking.UnscentedKalmanFilterParams beta(double beta)

model

@opencv_core.Ptr
public opencv_tracking.UkfSystemModel model()

Object of the class containing functions for computing the next state and the measurement.

model

public opencv_tracking.UnscentedKalmanFilterParams model(opencv_tracking.UkfSystemModel model)

init

public void init(int dp,
                 int mp,
                 int cp,
                 double processNoiseCovDiag,
                 double measurementNoiseCovDiag,
                 @opencv_core.Ptr
                 opencv_tracking.UkfSystemModel dynamicalSystem,
                 int type)

The function for initialization of Unscented Kalman filter

Parameters:

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.

init

public void init(int dp,
                 int mp,
                 int cp,
                 double processNoiseCovDiag,
                 double measurementNoiseCovDiag,
                 @opencv_core.Ptr
                 opencv_tracking.UkfSystemModel dynamicalSystem)