org.bytedeco.opencv.opencv_tracking

Class UnscentedKalmanFilterParams

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.opencv.opencv_tracking.UnscentedKalmanFilterParams

All Implemented Interfaces:

AutoCloseable

Direct Known Subclasses:

AugmentedUnscentedKalmanFilterParams

@Namespace(value="cv::detail::tracking::kalman_filters")
 @NoOffset
 @Properties(inherit=opencv_tracking.class)
public class UnscentedKalmanFilterParams
extends 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

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

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, UkfSystemModel dynamicalSystem)
UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, UkfSystemModel dynamicalSystem, int type)
UnscentedKalmanFilterParams(long size) Native array allocator.
UnscentedKalmanFilterParams(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
double	alpha() Default is 1e-3.
UnscentedKalmanFilterParams	alpha(double setter)
double	beta() Default is 2.0.
UnscentedKalmanFilterParams	beta(double setter)
int	CP() Dimensionality of the control vector.
UnscentedKalmanFilterParams	CP(int setter)
int	dataType() Type of elements of vectors and matrices, default is CV_64F.
UnscentedKalmanFilterParams	dataType(int setter)
int	DP() Dimensionality of the state vector.
UnscentedKalmanFilterParams	DP(int setter)
Mat	errorCovInit() State estimate cross-covariance matrix, DP x DP, default is identity.
UnscentedKalmanFilterParams	errorCovInit(Mat setter)
UnscentedKalmanFilterParams	getPointer(long i)
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
double	k() Default is 0.
UnscentedKalmanFilterParams	k(double setter)
Mat	measurementNoiseCov() Measurement noise cross-covariance matrix, MP x MP.
UnscentedKalmanFilterParams	measurementNoiseCov(Mat setter)
UkfSystemModel	model() Object of the class containing functions for computing the next state and the measurement.
UnscentedKalmanFilterParams	model(UkfSystemModel setter)
int	MP() Dimensionality of the measurement vector.
UnscentedKalmanFilterParams	MP(int setter)
UnscentedKalmanFilterParams	position(long position)
Mat	processNoiseCov() Process noise cross-covariance matrix, DP x DP.
UnscentedKalmanFilterParams	processNoiseCov(Mat setter)
Mat	stateInit() Initial state, DP x 1, default is zero.
UnscentedKalmanFilterParams	stateInit(Mat setter)

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, getPointer, getPointer, getPointer, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

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

Constructor Detail

UnscentedKalmanFilterParams

public UnscentedKalmanFilterParams(Pointer p)

Pointer cast constructor. Invokes 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
                                   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
                                   UkfSystemModel dynamicalSystem)

Method Detail

position

public UnscentedKalmanFilterParams position(long position)

Overrides:

position in class Pointer

getPointer

public UnscentedKalmanFilterParams getPointer(long i)

Overrides:

getPointer in class Pointer

DP

public int DP()

Dimensionality of the state vector.

DP

public UnscentedKalmanFilterParams DP(int setter)

MP

public int MP()

Dimensionality of the measurement vector.

MP

public UnscentedKalmanFilterParams MP(int setter)

CP

public int CP()

Dimensionality of the control vector.

CP

public UnscentedKalmanFilterParams CP(int setter)

dataType

public int dataType()

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

dataType

public UnscentedKalmanFilterParams dataType(int setter)

stateInit

@ByRef
public Mat stateInit()

Initial state, DP x 1, default is zero.

stateInit

public UnscentedKalmanFilterParams stateInit(Mat setter)

errorCovInit

@ByRef
public Mat errorCovInit()

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

errorCovInit

public UnscentedKalmanFilterParams errorCovInit(Mat setter)

processNoiseCov

@ByRef
public Mat processNoiseCov()

Process noise cross-covariance matrix, DP x DP.

processNoiseCov

public UnscentedKalmanFilterParams processNoiseCov(Mat setter)

measurementNoiseCov

@ByRef
public Mat measurementNoiseCov()

Measurement noise cross-covariance matrix, MP x MP.

measurementNoiseCov

public UnscentedKalmanFilterParams measurementNoiseCov(Mat setter)

alpha

public double alpha()

Default is 1e-3.

alpha

public UnscentedKalmanFilterParams alpha(double setter)

k

public double k()

Default is 0.

k

public UnscentedKalmanFilterParams k(double setter)

beta

public double beta()

Default is 2.0.

beta

public UnscentedKalmanFilterParams beta(double setter)

model

@opencv_core.Ptr
public UkfSystemModel model()

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

model

public UnscentedKalmanFilterParams model(UkfSystemModel setter)

init

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