com.irurueta.geometry.estimators.Point3DRobustEstimator

Direct Known Subclasses:: LMedSPoint3DRobustEstimator, MSACPoint3DRobustEstimator, PROMedSPoint3DRobustEstimator, PROSACPoint3DRobustEstimator, RANSACPoint3DRobustEstimator

public abstract class Point3DRobustEstimator extends Object

This is an abstract class for algorithms to robustly find the best 3D point that intersects in a collection of 3D planes. Implementations of this class should be able to detect and discard outliers in order to find the best solution.

Field Summary

Fields

Modifier and Type

Field

Description

protected double

confidence

Amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%).

private com.irurueta.algebra.Matrix

covariance

Estimated covariance of estimated 3D point.

static final double

DEFAULT_CONFIDENCE

Constant defining default confidence of the estimated result, which is 99%.

static final boolean

DEFAULT_KEEP_COVARIANCE

Indicates that covariance is not kept by default after refining result.

static final int

DEFAULT_MAX_ITERATIONS

Default maximum allowed number of iterations.

static final float

DEFAULT_PROGRESS_DELTA

Default amount of progress variation before notifying a change in estimation progress.

static final boolean

DEFAULT_REFINE_RESULT

Indicates that result is refined by default using Levenberg-Marquardt fitting algorithm over found inliers.

static final com.irurueta.numerical.robust.RobustEstimatorMethod

DEFAULT_ROBUST_METHOD

Default robust estimator method when none is provided.

protected com.irurueta.numerical.robust.InliersData

inliersData

Data related to inliers found after estimation.

private boolean

keepCovariance

Indicates whether covariance must be kept after refining result.

protected Point3DRobustEstimatorListener

listener

Listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

protected boolean

locked

Indicates if this estimator is locked because an estimation is being computed.

static final double

MAX_CONFIDENCE

Maximum allowed confidence value.

static final float

MAX_PROGRESS_DELTA

Maximum allowed value for progress delta.

protected int

maxIterations

Maximum allowed number of iterations.

static final double

MIN_CONFIDENCE

Minimum allowed confidence value.

static final int

MIN_ITERATIONS

Minimum allowed number of iterations.

static final float

MIN_PROGRESS_DELTA

Minimum allowed value for progress delta.

static final int

MINIMUM_SIZE

Minimum number of 3D planes required to estimate a point.

protected List<Plane>

planes

List of lines to be used to estimate a 3D point.

protected float

progressDelta

Amount of progress variation before notifying a progress change during estimation.

private CoordinatesType

refinementCoordinatesType

Coordinates type to use for refinement.

protected boolean

refineResult

Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers.
Constructor Summary

Constructors

Modifier

Constructor

Description

protected

Point3DRobustEstimator()

Constructor.

protected

Point3DRobustEstimator(Point3DRobustEstimatorListener listener)

Constructor.

protected

Point3DRobustEstimator(Point3DRobustEstimatorListener listener, List<Plane> planes)

Constructor.

protected

Point3DRobustEstimator(List<Plane> planes)

Constructor with lines.
Method Summary

Modifier and Type

Method

Description

protected Point3D

attemptRefine(Point3D point)

Attempts to refine provided solution if refinement is requested.

static Point3DRobustEstimator

create()

Creates a 3D point robust estimator based on 3D plane samples and using default robust estimator method.

static Point3DRobustEstimator

create(double[] qualityScores)

Creates a 3D point robust estimator based on 3D plane samples and using default robust estimator method.

static Point3DRobustEstimator

create(double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided robust estimator method.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and default robust estimator method.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, double[] qualityScores)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and default estimator method.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, List<Plane> planes)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes and default robust estimator method.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, List<Plane> planes, double[] qualityScores)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes and default estimator method.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, List<Plane> planes, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes.

static Point3DRobustEstimator

create(Point3DRobustEstimatorListener listener, List<Plane> planes, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes.

static Point3DRobustEstimator

create(com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D line samples and using provided robust estimator method.

static Point3DRobustEstimator

create(List<Plane> planes)

Creates a 3D point robust estimator based on 3D plane samples and using provided planes and default robust estimator method.

static Point3DRobustEstimator

create(List<Plane> planes, double[] qualityScores)

Creates a 3D point robust estimator based on 3D plane samples and using provided planes and default estimator method.

static Point3DRobustEstimator

create(List<Plane> planes, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided planes and robust estimator method.

static Point3DRobustEstimator

create(List<Plane> planes, com.irurueta.numerical.robust.RobustEstimatorMethod method)

Creates a 3D point robust estimator based on 3D plane samples and using provided planes and robust estimator method.

abstract Point3D

estimate()

Estimates a 3D point using a robust estimator and the best set of 3D planes that intersect into the estimated 3D point.

double

getConfidence()

Returns amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%).

com.irurueta.algebra.Matrix

getCovariance()

Gets estimated covariance of estimated 3D point if available.

com.irurueta.numerical.robust.InliersData

getInliersData()

Gets data related to inliers found after estimation.

Point3DRobustEstimatorListener

getListener()

Returns reference to listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

int

getMaxIterations()

Returns maximum allowed number of iterations.

abstract com.irurueta.numerical.robust.RobustEstimatorMethod

getMethod()

Returns method being used for robust estimation.

List<Plane>

getPlanes()

Returns list of planes to be used to estimate a 3D point.

float

getProgressDelta()

Returns amount of progress variation before notifying a progress change during estimation.

double[]

getQualityScores()

Returns quality scores corresponding to each line.

CoordinatesType

getRefinementCoordinatesType()

Gets coordinates type to use for refinement.

protected abstract double

getRefinementStandardDeviation()

Gets standard deviation used for Levenberg-Marquardt fitting during refinement.

private void

internalSetPlanes(List<Plane> planes)

Internal method to set list of 3D planes to be used to estimate a 3D point.

boolean

isCovarianceKept()

Indicates whether covariance must be kept after refining result.

boolean

isListenerAvailable()

Indicates whether listener has been provided and is available for retrieval.

boolean

isLocked()

Indicates if this instance is locked because estimation is being computed

boolean

isReady()

Indicates if estimator is ready to start the 3D point estimation.

boolean

isResultRefined()

Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers.

protected double

residual(Point3D p, Plane plane)

Computes the residual between a 3D point and a plane.

void

setConfidence(double confidence)

Sets amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%).

void

setCovarianceKept(boolean keepCovariance)

Specifies whether covariance must be kept after refining result.

void

setListener(Point3DRobustEstimatorListener listener)

Sets listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

void

setMaxIterations(int maxIterations)

Sets maximum allowed number of iterations.

void

setPlanes(List<Plane> planes)

Sets list of planes to be used to estimate a 3D point.

void

setProgressDelta(float progressDelta)

Sets amount of progress variation before notifying a progress change during estimation.

void

setQualityScores(double[] qualityScores)

Sets quality scores corresponding to each line.

void

setRefinementCoordinatesType(CoordinatesType refinementCoordinatesType)

Sets coordinates type to use for refinement.

void

setResultRefined(boolean refineResult)

Specifies whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details
- MINIMUM_SIZE
  
  public static final int MINIMUM_SIZE
  
  Minimum number of 3D planes required to estimate a point.
  See Also:
  
  Constant Field Values
- DEFAULT_PROGRESS_DELTA
  
  public static final float DEFAULT_PROGRESS_DELTA
  
  Default amount of progress variation before notifying a change in estimation progress. By default, this is set to 5%.
  See Also:
  
  Constant Field Values
- MIN_PROGRESS_DELTA
  
  public static final float MIN_PROGRESS_DELTA
  
  Minimum allowed value for progress delta.
  See Also:
  
  Constant Field Values
- MAX_PROGRESS_DELTA
  
  public static final float MAX_PROGRESS_DELTA
  
  Maximum allowed value for progress delta.
  See Also:
  
  Constant Field Values
- DEFAULT_CONFIDENCE
  
  public static final double DEFAULT_CONFIDENCE
  
  Constant defining default confidence of the estimated result, which is 99%. This means that with a probability of 99% estimation will be accurate because chosen sub-samples will be inliers.
  See Also:
  
  Constant Field Values
- DEFAULT_MAX_ITERATIONS
  
  public static final int DEFAULT_MAX_ITERATIONS
  
  Default maximum allowed number of iterations.
  See Also:
  
  Constant Field Values
- MIN_CONFIDENCE
  
  public static final double MIN_CONFIDENCE
  
  Minimum allowed confidence value.
  See Also:
  
  Constant Field Values
- MAX_CONFIDENCE
  
  public static final double MAX_CONFIDENCE
  
  Maximum allowed confidence value.
  See Also:
  
  Constant Field Values
- MIN_ITERATIONS
  
  public static final int MIN_ITERATIONS
  
  Minimum allowed number of iterations.
  See Also:
  
  Constant Field Values
- DEFAULT_ROBUST_METHOD
  
  public static final com.irurueta.numerical.robust.RobustEstimatorMethod DEFAULT_ROBUST_METHOD
  
  Default robust estimator method when none is provided.
- DEFAULT_REFINE_RESULT
  
  public static final boolean DEFAULT_REFINE_RESULT
  
  Indicates that result is refined by default using Levenberg-Marquardt fitting algorithm over found inliers.
  See Also:
  
  Constant Field Values
- DEFAULT_KEEP_COVARIANCE
  
  public static final boolean DEFAULT_KEEP_COVARIANCE
  
  Indicates that covariance is not kept by default after refining result.
  See Also:
  
  Constant Field Values
- listener
  
  protected Point3DRobustEstimatorListener listener
  
  Listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
- locked
  
  protected volatile boolean locked
  
  Indicates if this estimator is locked because an estimation is being computed.
- progressDelta
  
  protected float progressDelta
  
  Amount of progress variation before notifying a progress change during estimation.
- confidence
  
  protected double confidence
  
  Amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.
- maxIterations
  
  protected int maxIterations
  
  Maximum allowed number of iterations. When the maximum number of iterations is exceeded, result will not be available, however an approximate result will be available for retrieval.
- planes
  
  protected List<Plane> planes
  
  List of lines to be used to estimate a 3D point. Provided list must have a size greater or equal than MINIMUM_SIZE.
- inliersData
  
  protected com.irurueta.numerical.robust.InliersData inliersData
  
  Data related to inliers found after estimation.
- refineResult
  
  protected boolean refineResult
  
  Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers. If true, inliers will be computed and kept in any implementation regardless of the settings.
- refinementCoordinatesType
  
  private CoordinatesType refinementCoordinatesType
  
  Coordinates type to use for refinement. When using inhomogeneous coordinates a 3x3 covariance matrix is estimated. When using homogeneous coordinates a 4x4 covariance matrix is estimated.
- keepCovariance
  
  private boolean keepCovariance
  
  Indicates whether covariance must be kept after refining result. This setting is only taken into account if result is refined.
- covariance
  
  private com.irurueta.algebra.Matrix covariance
  
  Estimated covariance of estimated 3D point. This is only available when result has been refined and covariance is kept.
Constructor Details
- Point3DRobustEstimator
  
  protected Point3DRobustEstimator()
  
  Constructor.
- Point3DRobustEstimator
  
  protected Point3DRobustEstimator(Point3DRobustEstimatorListener listener)
  
  Constructor.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
- Point3DRobustEstimator
  
  protected Point3DRobustEstimator(List<Plane> planes)
  
  Constructor with lines.
  
  Parameters:
  
  planes - 3D planes to estimate a 3D point.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.
- Point3DRobustEstimator
  
  protected Point3DRobustEstimator(Point3DRobustEstimatorListener listener, List<Plane> planes)
  
  Constructor.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  planes - 3D planes to estimate a 3D point.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.
Method Details
- getListener
  
  public Point3DRobustEstimatorListener getListener()
  
  Returns reference to listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  Returns:
  
  listener to be notified of events.
- setListener
  
  public void setListener(Point3DRobustEstimatorListener listener) throws LockedException
  
  Sets listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  Parameters:
  
  listener - listener to be notified of events.
  
  Throws:
  
  LockedException - if robust estimator is locked.
- isListenerAvailable
  
  public boolean isListenerAvailable()
  
  Indicates whether listener has been provided and is available for retrieval.
  
  Returns:
  
  true if available, false otherwise.
- isLocked
  
  public boolean isLocked()
  
  Indicates if this instance is locked because estimation is being computed
  
  Returns:
  
  true if locked, false otherwise.
- getProgressDelta
  
  public float getProgressDelta()
  
  Returns amount of progress variation before notifying a progress change during estimation.
  
  Returns:
  
  amount of progress variation before notifying a progress change during estimation.
- setProgressDelta
  
  public void setProgressDelta(float progressDelta) throws LockedException
  
  Sets amount of progress variation before notifying a progress change during estimation.
  
  Parameters:
  
  progressDelta - amount of progress variation before notifying a progress change during estimation.
  
  Throws:
  
  IllegalArgumentException - if progress delta is less than zero or greater than 1.
  
  LockedException - if this estimator is locked because an estimation is being computed.
- getConfidence
  
  public double getConfidence()
  
  Returns amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.
  
  Returns:
  
  amount of confidence as a value between 0.0 and 1.0.
- setConfidence
  
  public void setConfidence(double confidence) throws LockedException
  
  Sets amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.
  
  Parameters:
  
  confidence - confidence to be set as a value between 0.0 and 1.0.
  
  Throws:
  
  IllegalArgumentException - if provided value is not between 0.0 and 1.0.
  
  LockedException - if this estimator is locked because an estimator is being computed.
- getMaxIterations
  
  public int getMaxIterations()
  
  Returns maximum allowed number of iterations. If maximum allowed number of iterations is achieved without converging to a result when calling estimate(), a RobustEstimatorException will be raised.
  
  Returns:
  
  maximum allowed number of iterations.
- setMaxIterations
  
  public void setMaxIterations(int maxIterations) throws LockedException
  
  Sets maximum allowed number of iterations. When the maximum number of iterations is exceeded, result will not be available, however an approximate result will be available for retrieval.
  
  Parameters:
  
  maxIterations - maximum allowed number of iterations to be set.
  
  Throws:
  
  IllegalArgumentException - if provided value is less than 1.
  
  LockedException - if this estimator is locked because an estimation is being computed.
- getInliersData
  
  public com.irurueta.numerical.robust.InliersData getInliersData()
  
  Gets data related to inliers found after estimation.
  
  Returns:
  
  data related to inliers found after estimation.
- isResultRefined
  
  public boolean isResultRefined()
  
  Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers. If true, inliers will be computed and kept in any implementation regardless of the settings.
  
  Returns:
  
  true to refine result, false to simply use result found by robust estimator without further refining.
- setResultRefined
  
  public void setResultRefined(boolean refineResult) throws LockedException
  
  Specifies whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers.
  
  Parameters:
  
  refineResult - true to refine result, false to simply use result found by robust estimator without further refining.
  
  Throws:
  
  LockedException - if estimator is locked.
- getRefinementCoordinatesType
  
  public CoordinatesType getRefinementCoordinatesType()
  
  Gets coordinates type to use for refinement. When using inhomogeneous coordinates a 3x3 covariance matrix is estimated. When using homogeneous coordinates a 4x4 covariance matrix is estimated.
  
  Returns:
  
  coordinates type to use for refinement.
- setRefinementCoordinatesType
  
  public void setRefinementCoordinatesType(CoordinatesType refinementCoordinatesType) throws LockedException
  
  Sets coordinates type to use for refinement. When using inhomogeneous coordinates a 3x3 covariance matrix is estimated. When using homogeneous coordinates a 4x4 covariance matrix is estimated.
  
  Parameters:
  
  refinementCoordinatesType - coordinates type to use for refinement.
  
  Throws:
  
  LockedException - if estimator is locked.
- isCovarianceKept
  
  public boolean isCovarianceKept()
  
  Indicates whether covariance must be kept after refining result. This setting is only taken into account if result is refined.
  
  Returns:
  
  true if covariance must be kept after refining result, false otherwise.
- setCovarianceKept
  
  public void setCovarianceKept(boolean keepCovariance) throws LockedException
  
  Specifies whether covariance must be kept after refining result. This setting is only taken into account if result is refined.
  
  Parameters:
  
  keepCovariance - true if covariance must be kept after refining result, false otherwise.
  
  Throws:
  
  LockedException - if estimator is locked.
- getPlanes
  
  public List<Plane> getPlanes()
  
  Returns list of planes to be used to estimate a 3D point. Provided list must have a size greater or equal than MINIMUM_SIZE.
  
  Returns:
  
  list of planes to be used to estimate a 3D point.
- setPlanes
  
  public void setPlanes(List<Plane> planes) throws LockedException
  
  Sets list of planes to be used to estimate a 3D point. Provided list must have a size greater or equal than MINIMUM_SIZE.
  
  Parameters:
  
  planes - list of planes to be used to estimate a 3D point.
  
  Throws:
  
  IllegalArgumentException - if provided list of planes doesn't have a size greater or equal than MINIMUM_SIZE.
  
  LockedException - if estimator is locked because a computation is already in progress.
- isReady
  
  public boolean isReady()
  
  Indicates if estimator is ready to start the 3D point estimation. This is true when a minimum if MINIMUM_SIZE lines are available.
  
  Returns:
  
  true if estimator is ready, false otherwise.
- getQualityScores
  
  public double[] getQualityScores()
  
  Returns quality scores corresponding to each line. The larger the score value the better the quality of the line measure. This implementation always returns null. Subclasses using quality scores must implement proper behaviour.
  
  Returns:
  
  quality scores corresponding to each point.
- setQualityScores
  
  public void setQualityScores(double[] qualityScores) throws LockedException
  
  Sets quality scores corresponding to each line. The larger the score value the better the quality of the line measure. This implementation makes no action. Subclasses using quality scores must implement proper behaviour.
  
  Parameters:
  
  qualityScores - quality scores corresponding to each sampled line.
  
  Throws:
  
  LockedException - if robust estimator is locked because an estimation is already in progress.
  
  IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).
- getCovariance
  
  public com.irurueta.algebra.Matrix getCovariance()
  
  Gets estimated covariance of estimated 3D point if available. This is only available when result has been refined and covariance is kept.
  
  Returns:
  
  estimated covariance or null.
- create
  
  public static Point3DRobustEstimator create(com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D line samples and using provided robust estimator method.
  
  Parameters:
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
- create
  
  public static Point3DRobustEstimator create(List<Plane> planes, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided planes and robust estimator method.
  
  Parameters:
  
  planes - 3D planes to estimate a 3D point.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, List<Plane> planes, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  planes - 3D planes to estimate a 3D point.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided robust estimator method.
  
  Parameters:
  
  qualityScores - quality scores corresponding to each provided plane.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 2 lines).
- create
  
  public static Point3DRobustEstimator create(List<Plane> planes, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided planes and robust estimator method.
  
  Parameters:
  
  planes - 3D planes to estimate a 3D point.
  
  qualityScores - quality scores corresponding to each provided plane.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines doesn't have the same size as the list of provided quality scores, or it their size is not greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  qualityScores - quality scores corresponding to each provided plane.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 2 lines).
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, List<Plane> planes, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  planes - 3D planes to estimate a 3D point.
  
  qualityScores - quality scores corresponding to each provided point.
  
  method - method of a robust estimator algorithm to estimate the best 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of planes doesn't have the same size as the list of provided quality scores, or it their size is not greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create()
  
  Creates a 3D point robust estimator based on 3D plane samples and using default robust estimator method.
  
  Returns:
  
  an instance of a 3D point robust estimator.
- create
  
  public static Point3DRobustEstimator create(List<Plane> planes)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided planes and default robust estimator method.
  
  Parameters:
  
  planes - 3D planes to estimate a 3D point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines doesn't have a size greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and default robust estimator method.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  Returns:
  
  an instance of a 3D point robust estimator.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, List<Plane> planes)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes and default robust estimator method.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  planes - 3D planes to estimate a point.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(double[] qualityScores)
  
  Creates a 3D point robust estimator based on 3D plane samples and using default robust estimator method.
  
  Parameters:
  
  qualityScores - quality scores corresponding to each provided plane
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 planes).
- create
  
  public static Point3DRobustEstimator create(List<Plane> planes, double[] qualityScores)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided planes and default estimator method.
  
  Parameters:
  
  planes - 3D planes to estimate a 3D point.
  
  qualityScores - quality scores corresponding to each provided plane.
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of planes doesn't have the same size as the list of provided quality scores, or if their size is not greater or equal than MINIMUM_SIZE.
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, double[] qualityScores)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and default estimator method.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  qualityScores - quality scores corresponding to each provided plane
  
  Returns:
  
  an instance of a circle robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 planes).
- create
  
  public static Point3DRobustEstimator create(Point3DRobustEstimatorListener listener, List<Plane> planes, double[] qualityScores)
  
  Creates a 3D point robust estimator based on 3D plane samples and using provided listener and planes and default estimator method.
  
  Parameters:
  
  listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
  
  planes - 3D planes to estimate a 3D point.
  
  qualityScores - quality scores corresponding to each provided plane
  
  Returns:
  
  an instance of a 3D point robust estimator.
  
  Throws:
  
  IllegalArgumentException - if provided list of lines don't have the same size as the list of provided quality scores, or if their size is not greater or equal than MINIMUM_SIZE.
- estimate
  
  public abstract Point3D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
  
  Estimates a 3D point using a robust estimator and the best set of 3D planes that intersect into the estimated 3D point.
  
  Returns:
  
  a 3D point.
  
  Throws:
  
  LockedException - if robust estimator is locked because an estimation is already in progress.
  
  NotReadyException - if provided input data is not enough to start the estimation.
  
  com.irurueta.numerical.robust.RobustEstimatorException - if estimation fails for any reason (i.e. numerical instability, no solution available, etc).
- getMethod
  
  public abstract com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()
  
  Returns method being used for robust estimation.
  
  Returns:
  
  method being used for robust estimation.
- residual
  
  protected double residual(Point3D p, Plane plane)
  
  Computes the residual between a 3D point and a plane.
  
  Parameters:
  
  p - a 3D point.
  
  plane - a 3D plane.
  
  Returns:
  
  residual.
- attemptRefine
  
  protected Point3D attemptRefine(Point3D point)
  
  Attempts to refine provided solution if refinement is requested. This method returns a refined solution or the same provided solution if refinement is not requested or has failed. If refinement is enabled, and it is requested to keep covariance, this method will also keep covariance of refined point.
  
  Parameters:
  
  point - point estimated by a robust estimator without refinement.
  
  Returns:
  
  solution after refinement (if requested) or the provided non-refined solution if not requested or if refinement failed.
- getRefinementStandardDeviation
  
  protected abstract double getRefinementStandardDeviation()
  
  Gets standard deviation used for Levenberg-Marquardt fitting during refinement. Returned value gives an indication of how much variance each residual has. Typically, this value is related to the threshold used on each robust estimation, since residuals of found inliers are within the range of such threshold.
  
  Returns:
  
  standard deviation used for refinement.
- internalSetPlanes
  
  private void internalSetPlanes(List<Plane> planes)
  
  Internal method to set list of 3D planes to be used to estimate a 3D point. This method does not check whether estimator is locked or not.
  
  Parameters:
  
  planes - list of planes to be used to estimate a 3D point.
  
  Throws:
  
  IllegalArgumentException - if provided list of planes doesn't have a size greater or equal than MINIMUM_SIZE.

Class Point3DRobustEstimator

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Details

MINIMUM_SIZE

DEFAULT_PROGRESS_DELTA

MIN_PROGRESS_DELTA

MAX_PROGRESS_DELTA

DEFAULT_CONFIDENCE

DEFAULT_MAX_ITERATIONS

MIN_CONFIDENCE

MAX_CONFIDENCE

MIN_ITERATIONS

DEFAULT_ROBUST_METHOD

DEFAULT_REFINE_RESULT

DEFAULT_KEEP_COVARIANCE

listener

locked

progressDelta

confidence

maxIterations

planes

inliersData

refineResult

refinementCoordinatesType

keepCovariance

covariance

Constructor Details

Point3DRobustEstimator

Point3DRobustEstimator

Point3DRobustEstimator

Point3DRobustEstimator

Method Details

getListener

setListener

isListenerAvailable

isLocked

getProgressDelta

setProgressDelta

getConfidence

setConfidence

getMaxIterations

setMaxIterations

getInliersData

isResultRefined

setResultRefined

getRefinementCoordinatesType

setRefinementCoordinatesType

isCovarianceKept

setCovarianceKept

getPlanes

setPlanes

isReady

getQualityScores

setQualityScores

getCovariance

create

create

create

create

create

create

create

create

create

create

create

create

create

create

create

create

estimate

getMethod

residual

attemptRefine

getRefinementStandardDeviation

internalSetPlanes