@ALDAOperator(genericExecutionMode=NONE,
level=STANDARD)
public class MultiObservationGenerator
extends de.unihalle.informatik.Alida.operator.ALDOperator
Modifier and Type | Class and Description |
---|---|
class |
MultiObservationGenerator.GeneratorInfo |
Modifier and Type | Field and Description |
---|---|
double |
delta_t |
MultiObservationGenerator.GeneratorInfo |
genInfo |
double |
lambdaBirth |
double |
lambdaClutter |
double |
lambdaDeath |
int |
maxTargetID |
Jama.Matrix |
modelTransition |
short |
nInitialTargets |
int |
nTimesteps |
protected Vector<MultiState<MotionModelID>> |
observations |
protected ExponentialDistribution |
Pdeath |
double |
pDetect |
double |
qsize |
double |
qxy |
double |
qxy_ |
protected Random |
rand |
long |
randomSeed |
double |
rsize |
double |
rxy |
double |
sqrtSizeMax |
double |
sqrtSizeMin |
double |
xMax |
double |
xMin |
double |
yMax |
double |
yMin |
Constructor and Description |
---|
MultiObservationGenerator() |
Modifier and Type | Method and Description |
---|---|
protected LinearTransformGaussNoise[] |
createDynamicModels() |
protected MultiState<MotionModelID> |
createInitialStates() |
protected LinearTransformGaussNoise |
createObservationModel() |
protected MultiState<MotionModelID> |
generateNextStates(MultiState<MotionModelID> X,
LinearTransformGaussNoise[] dynamicModels) |
protected MultiState<MotionModelID> |
generateObservations(MultiState<MotionModelID> states,
LinearTransformGaussNoise obsModel,
MultiStateFactory<MotionModelID> obsFactory) |
Vector<MultiState<MotionModelID>> |
getObservations() |
protected boolean |
obsConflict(Jama.Matrix z,
MultiState<MotionModelID> Z) |
protected void |
operate() |
protected boolean |
stateConflict(Jama.Matrix x,
MultiState<MotionModelID> X) |
addOperatorExecutionProgressEventListener, addParameter, addParameter, addParameterUnconditioned, fieldContained, fireOperatorExecutionProgressEvent, getALDPortHashAccessKey, getConstructionMode, getDocumentation, getHidingMode, getInactiveParameterNames, getInInoutNames, getInInoutNames, getInNames, getInOutNames, getMissingRequiredInputs, getName, getNumParameters, getOutInoutNames, getOutNames, getParameter, getParameterDescriptor, getParameterDescriptorUnconditioned, getParameterNames, getParameterUnconditioned, getSupplementalNames, getVerbose, getVersion, handleOperatorExecutionProgressEvent, hasInOutParameters, hasParameter, isAnnotatedParameter, isConfigured, print, print, print, printInterface, printInterface, readHistory, readResolve, reinitializeParameterDescriptors, removeOperatorExecutionProgressEventListener, removeParameter, runOp, runOp, runOp, setConstructionMode, setConstructionMode, setConstructionMode, setHidingMode, setName, setParameter, setParameterUnconditioned, setVerbose, toStringVerbose, unconfiguredItems, validate, validateCustom, validateGeneric, writeHistory, writeHistory, writeHistory
@Parameter(label="observations", required=false, direction=OUT, description="Generated observations") protected Vector<MultiState<MotionModelID>> observations
@Parameter(label="pDetect", required=true, direction=IN, description="Probability of detecting a target") public double pDetect
@Parameter(label="lambdaClutter", required=true, direction=IN, description="Mean/variance of the Poisson distribution of the number of clutter observations") public double lambdaClutter
@Parameter(label="lambdaBirth", required=true, direction=IN, description="Mean/variance of the Poisson distribution of the number of newborn targets") public double lambdaBirth
@Parameter(label="lambdaDeath", required=true, direction=IN, description="Parameter of the exponential distribution of the survival of nonassociated targets") public double lambdaDeath
@Parameter(label="delta_t", required=false, direction=IN, description="time interval between two frames") public double delta_t
@Parameter(label="xMin", required=true, direction=IN, description="x-min of the rectangular region where the observations reside in (e.g. for image creation)") public double xMin
@Parameter(label="yMin", required=true, direction=IN, description="y-min of the rectangular region where the observations reside in (e.g. for image creation)") public double yMin
@Parameter(label="xMax", required=true, direction=IN, description="x-max of the rectangular region where the observations reside in (e.g. for image creation)") public double xMax
@Parameter(label="yMax", required=true, direction=IN, description="y-max of the rectangular region where the observations reside in (e.g. for image creation)") public double yMax
@Parameter(label="minSqrtSize", required=true, direction=IN, description="Minimum radius for newborn observations") public double sqrtSizeMin
@Parameter(label="maxSqrtSize", required=true, direction=IN, description="Maximum sqrt(size) for newborn observations") public double sqrtSizeMax
@Parameter(label="nTimesteps", required=true, direction=IN, description="Number of time steps (frames)") public int nTimesteps
@Parameter(label="nInitialTargets", required=true, direction=IN, description="Number of initial targets") public short nInitialTargets
@Parameter(label="modelTransition", required=true, direction=IN, description="A 2x2 markov matrix with probabilities of changing the dynamic models from time t-1 to t") public Jama.Matrix modelTransition
@Parameter(label="qxy", required=true, direction=IN, description="Variance of the current x-/y-position in the process noise covariance matrix") public double qxy
@Parameter(label="qxy_", required=true, direction=IN, description="Variance of the last x-/y-position in the process noise covariance matrix") public double qxy_
@Parameter(label="qsize", required=true, direction=IN, description="Variance of sqrt(size) in the process noise covariance matrix") public double qsize
@Parameter(label="rxy", required=true, direction=IN, description="Variance of the current x-/y-position in the measurement noise covariance matrix") public double rxy
@Parameter(label="rsize", required=true, direction=IN, description="Variance of sqrt(size) in the measurement noise covariance matrix") public double rsize
@Parameter(label="randomSeed", required=true, direction=IN, description="A seed for the random number generator") public long randomSeed
@Parameter(label="genInfo", required=false, direction=OUT, description="Information about the generated observations") public MultiObservationGenerator.GeneratorInfo genInfo
protected Random rand
protected ExponentialDistribution Pdeath
public int maxTargetID
public MultiObservationGenerator() throws de.unihalle.informatik.Alida.exceptions.ALDOperatorException
de.unihalle.informatik.Alida.exceptions.ALDOperatorException
public Vector<MultiState<MotionModelID>> getObservations()
protected void operate() throws de.unihalle.informatik.Alida.exceptions.ALDOperatorException, de.unihalle.informatik.Alida.exceptions.ALDProcessingDAGException
operate
in class de.unihalle.informatik.Alida.operator.ALDOperator
de.unihalle.informatik.Alida.exceptions.ALDOperatorException
de.unihalle.informatik.Alida.exceptions.ALDProcessingDAGException
protected LinearTransformGaussNoise[] createDynamicModels()
protected LinearTransformGaussNoise createObservationModel()
protected MultiState<MotionModelID> createInitialStates()
protected MultiState<MotionModelID> generateObservations(MultiState<MotionModelID> states, LinearTransformGaussNoise obsModel, MultiStateFactory<MotionModelID> obsFactory)
protected MultiState<MotionModelID> generateNextStates(MultiState<MotionModelID> X, LinearTransformGaussNoise[] dynamicModels)
protected boolean stateConflict(Jama.Matrix x, MultiState<MotionModelID> X)
protected boolean obsConflict(Jama.Matrix z, MultiState<MotionModelID> Z)
Copyright © 2010–2020 Martin Luther University Halle-Wittenberg, Institute of Computer Science, Pattern Recognition and Bioinformatics. All rights reserved.