Package com.irurueta.ar.calibration.estimators

Class ImageOfAbsoluteConicRobustEstimator

java.lang.Object
com.irurueta.ar.calibration.estimators.ImageOfAbsoluteConicRobustEstimator
Direct Known Subclasses:
LMedSImageOfAbsoluteConicRobustEstimator, MSACImageOfAbsoluteConicRobustEstimator, PROMedSImageOfAbsoluteConicRobustEstimator, PROSACImageOfAbsoluteConicRobustEstimator, RANSACImageOfAbsoluteConicRobustEstimator
public abstract class ImageOfAbsoluteConicRobustEstimator extends Object
This is an abstract class for algorithms to robustly find the best ImageOfAbsoluteConic (IAC) for provided collection of 2D homographies. Implementions 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%).
    static final double
    DEFAULT_CONFIDENCE
    Constant defining default confidence of the estimated result, which is 99%.
    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 com.irurueta.numerical.robust.RobustEstimatorMethod
    DEFAULT_ROBUST_METHOD
    Default robust estimator method when none is provided.
    private com.irurueta.algebra.Matrix
    homMatrix
    Matrix representation of an homography.
    protected List<com.irurueta.geometry.Transformation2D>
    homographies
    Homographies to estimate image of absolute conic (IAC).
    protected final LMSEImageOfAbsoluteConicEstimator
    iacEstimator
    Internal non-robust estimator of IAC.
    private com.irurueta.algebra.Matrix
    iacMatrix
    IAC matrix for one iteration of the robust estimator.
    protected ImageOfAbsoluteConicRobustEstimatorListener
    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.
    private com.irurueta.algebra.Matrix
    mult1
    Product multiplication of IAC by the right term.
    protected float
    progressDelta
    Amount of progress variation before notifying a progress change during estimation.
    private double[]
    subMatrixLeft
    Sub-matrix of homography used as the left term on a matrix multiplication.
    private com.irurueta.algebra.Matrix
    subMatrixRight
    Sub-matrix of homography used as the right term on a matrix multiplication.

  • Constructor Summary

    Constructors
    Modifier
    Constructor
    Description
    protected
    ImageOfAbsoluteConicRobustEstimator()
    Constructor.
    protected
    ImageOfAbsoluteConicRobustEstimator(ImageOfAbsoluteConicRobustEstimatorListener listener)
    Constructor.
    protected
    ImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies)
    Constructor.
    protected
    ImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies, ImageOfAbsoluteConicRobustEstimatorListener listener)
    Constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    static ImageOfAbsoluteConicRobustEstimator
    create()
    Creates an image of absolute conic robust estimator using default method.
    static ImageOfAbsoluteConicRobustEstimator
    create(com.irurueta.numerical.robust.RobustEstimatorMethod method)
    Creates an image of absolute conic robust estimator using provided method.
    static ImageOfAbsoluteConicRobustEstimator
    create(List<com.irurueta.geometry.Transformation2D> homographies)
    Creates an image of absolute conic robust estimator using provided homographies.
    static ImageOfAbsoluteConicRobustEstimator
    create(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores)
    Creates an image of absolute conic robust estimator using provided homographies.
    static ImageOfAbsoluteConicRobustEstimator
    create(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
    Creates an image of absolute conic robust estimator using provided homographies.
    static ImageOfAbsoluteConicRobustEstimator
    create(List<com.irurueta.geometry.Transformation2D> homographies, com.irurueta.numerical.robust.RobustEstimatorMethod method)
    Creates an image of absolute conic robust estimator using provided homographies.
    abstract ImageOfAbsoluteConic
    estimate()
    Estimates Image of Absolute Conic (IAC).
    double
    getConfidence()
    Returns amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%).
    double
    getFocalDistanceAspectRatio()
    Returns aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance).
    List<com.irurueta.geometry.Transformation2D>
    getHomographies()
    Gets list of homographies to estimate IAC.
    ImageOfAbsoluteConicRobustEstimatorListener
    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.
    int
    getMinNumberOfRequiredHomographies()
    Returns minimum number of required homographies needed to estimate the Imag eof Absolute Conic (IAC).
    float
    getProgressDelta()
    Returns amount of progress variation before notifying a progress change during estimation.
    double[]
    getQualityScores()
    Returns quality scores corresponding to each homography.
    private void
    internalSetHomographies(List<com.irurueta.geometry.Transformation2D> homographies)
    Sets list of homographies.
    boolean
    isFocalDistanceAspectRatioKnown()
    Returns boolean indicating whether aspect ratio of focal distances (i.e.
    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
    isPrincipalPointAtOrigin()
    Returns boolean indicating whether principal point is assumed to be at origin of coordinates or not.
    boolean
    isReady()
    Returns value indicating whether required data has been provided so that IAC estimation can start.
    boolean
    isZeroSkewness()
    Returns boolean indicating whether camera skewness is assumed to be zero or not.
    protected double
    residual(ImageOfAbsoluteConic iac, com.irurueta.geometry.Transformation2D homography)
    Computes the residual between an image of absolute conic (IAC) and a 2D transformation (homography).
    void
    setConfidence(double confidence)
    Sets amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%).
    void
    setFocalDistanceAspectRatio(double focalDistanceAspectRatio)
    Sets aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance).
    void
    setFocalDistanceAspectRatioKnown(boolean focalDistanceAspectRatioKnown)
    Sets boolean indicating whether aspect ratio of focal distances (i.e.
    void
    setHomographies(List<com.irurueta.geometry.Transformation2D> homographies)
    Sets list of homographies to estimate IAC.
    void
    setListener(ImageOfAbsoluteConicRobustEstimatorListener 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
    setPrincipalPointAtOrigin(boolean principalPointAtOrigin)
    Sets boolean indicating whether principal point is assumed to be at origin of coordinates or not.
    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 homography.
    void
    setZeroSkewness(boolean zeroSkewness)
    Sets boolean indicating whether camera skewness is assumed to be zero or not.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Field Details

    • DEFAULT_ROBUST_METHOD

      public static final com.irurueta.numerical.robust.RobustEstimatorMethod DEFAULT_ROBUST_METHOD
      Default robust estimator method when none is provided. In general for IAC estimation is best to use PROSAC or RANSAC than any other method, as it provides more robust results.

    • 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:

    • MIN_PROGRESS_DELTA

      public static final float MIN_PROGRESS_DELTA
      Minimum allowed value for progress delta.
      See Also:

    • MAX_PROGRESS_DELTA

      public static final float MAX_PROGRESS_DELTA
      Maximum allowed value for progress delta.
      See Also:

    • 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:

    • DEFAULT_MAX_ITERATIONS

      public static final int DEFAULT_MAX_ITERATIONS
      Default maximum allowed number of iterations.
      See Also:

    • MIN_CONFIDENCE

      public static final double MIN_CONFIDENCE
      Minimum allowed confidence value.
      See Also:

    • MAX_CONFIDENCE

      public static final double MAX_CONFIDENCE
      Maximum allowed confidence value.
      See Also:

    • MIN_ITERATIONS

      public static final int MIN_ITERATIONS
      Minimum allowed number of iterations.
      See Also:

    • homographies

      protected List<com.irurueta.geometry.Transformation2D> homographies
      Homographies to estimate image of absolute conic (IAC).

    • iacEstimator

      protected final LMSEImageOfAbsoluteConicEstimator iacEstimator
      Internal non-robust estimator of IAC.

    • listener

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

    • locked

      protected 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.

    • iacMatrix

      private com.irurueta.algebra.Matrix iacMatrix
      IAC matrix for one iteration of the robust estimator. This is used during residuals estimation. This instance is reused for performance reasons.

    • homMatrix

      private com.irurueta.algebra.Matrix homMatrix
      Matrix representation of an homography. This is used during residuals estimation. This instance is reused for performance reasons.

    • subMatrixLeft

      private double[] subMatrixLeft
      Sub-matrix of homography used as the left term on a matrix multiplication. This is used during residuals estimation. This instance is reused for performance reasons.

    • subMatrixRight

      private com.irurueta.algebra.Matrix subMatrixRight
      Sub-matrix of homography used as the right term on a matrix multiplication. This is used during residuals estimation. This instance is reused for performance reasons.

    • mult1

      private com.irurueta.algebra.Matrix mult1
      Product multiplication of IAC by the right term. This is used during residuals estimation. This instance is reused for performance reasons.

  • Constructor Details

    • ImageOfAbsoluteConicRobustEstimator

      protected ImageOfAbsoluteConicRobustEstimator()
      Constructor.

    • ImageOfAbsoluteConicRobustEstimator

      protected ImageOfAbsoluteConicRobustEstimator(ImageOfAbsoluteConicRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • ImageOfAbsoluteConicRobustEstimator

      protected ImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies)
      Constructor.
      Parameters:
      homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.
      Throws:
      IllegalArgumentException - if not enough homographies are provided for default settings. Hence, at least 1 homography must be provided.

    • ImageOfAbsoluteConicRobustEstimator

      protected ImageOfAbsoluteConicRobustEstimator(List<com.irurueta.geometry.Transformation2D> homographies, ImageOfAbsoluteConicRobustEstimatorListener listener)
      Constructor.
      Parameters:
      homographies - list of homographies (2D transformations) used to estimate the image of absolute conic (IAC), which can be used to obtain pinhole camera intrinsic parameters.
      listener - listener to be notified of events such as when estimation starts, ends or estimation progress changes.
      Throws:
      IllegalArgumentException - if not enough homographies are provided for default settings. Hence, at least 1 homography must be provided.

  • Method Details

    • isZeroSkewness

      public boolean isZeroSkewness()
      Returns boolean indicating whether camera skewness is assumed to be zero or not. Skewness determines whether LCD sensor cells are properly aligned or not, where zero indicates perfect alignment. Typically, skewness is a value equal or very close to zero.
      Returns:
      true if camera skewness is assumed to be zero, otherwise camera skewness is estimated.

    • setZeroSkewness

      public void setZeroSkewness(boolean zeroSkewness) throws com.irurueta.geometry.estimators.LockedException
      Sets boolean indicating whether camera skewness is assumed to be zero or not. Skewness determines whether LCD sensor cells are properly aligned or not, where zero indicates perfect alignment. Typically, skewness is a value equal or very close to zero.
      Parameters:
      zeroSkewness - true if camera skewness is assumed to be zero, otherwise camera skewness is estimated.
      Throws:
      com.irurueta.geometry.estimators.LockedException - if estimator is locked.

    • isPrincipalPointAtOrigin

      public boolean isPrincipalPointAtOrigin()
      Returns boolean indicating whether principal point is assumed to be at origin of coordinates or not. Typically principal point is located at image center (origin of coordinates), and usually matches the center of radial distortion if it is taken into account.
      Returns:
      true if principal point is assumed to be at origin of coordinates, false if principal point must be estimated.

    • setPrincipalPointAtOrigin

      public void setPrincipalPointAtOrigin(boolean principalPointAtOrigin) throws com.irurueta.geometry.estimators.LockedException
      Sets boolean indicating whether principal point is assumed to be at origin of coordinates or not. Typically principal point is located at image center (origin of coordinates), and usually matches the center of radial distortion if it is taken into account.
      Parameters:
      principalPointAtOrigin - true if principal point is assumed to bet at origin of coordinates, false if principal point must be estimated
      Throws:
      com.irurueta.geometry.estimators.LockedException - if estimator is locked.

    • isFocalDistanceAspectRatioKnown

      public boolean isFocalDistanceAspectRatioKnown()
      Returns boolean indicating whether aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance) is known or not. Notice that focal distance aspect ratio is not related to image size aspect ratio. Typically, LCD sensor cells are square and hence aspect ratio of focal distances is known and equal to 1. This value is only taken into account if skewness is assumed to be zero, otherwise it is ignored.
      Returns:
      true if focal distance aspect ratio is known, false otherwise.

    • setFocalDistanceAspectRatioKnown

      public void setFocalDistanceAspectRatioKnown(boolean focalDistanceAspectRatioKnown) throws com.irurueta.geometry.estimators.LockedException
      Sets boolean indicating whether aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance) is known or not. Notice that focal distance aspect ratio is not related to image size aspect ratio. Typically, LCD sensor cells are square and hence aspect ratio of focal distances is known and equal to 1. This value is only taken into account if skewness is assumed to be zero, otherwise it is ignored.
      Parameters:
      focalDistanceAspectRatioKnown - true if focal distance aspect ratio is known, false otherwise.
      Throws:
      com.irurueta.geometry.estimators.LockedException - if estimator is locked.

    • getFocalDistanceAspectRatio

      public double getFocalDistanceAspectRatio()
      Returns aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance). This value is only taken into account if skewness is assumed to be zero and focal distance aspect ratio is marked as known, otherwise it is ignored. By default, this is 1.0, since it is taken into account that typically LCD sensor cells are square and hence aspect ratio focal distances is known and equal to 1. Notice that focal distance aspect ratio is not related to image size aspect ratio. Notice that a negative aspect ratio indicates that vertical axis is reversed. This can be useful in some situations where image vertical coordinates are reversed respect to the physical world (i.e. in computer graphics typically image vertical coordinates go downwards, while in physical world they go upwards).
      Returns:
      aspect ratio of focal distances.

    • setFocalDistanceAspectRatio

      public void setFocalDistanceAspectRatio(double focalDistanceAspectRatio) throws com.irurueta.geometry.estimators.LockedException
      Sets aspect ratio of focal distances (i.e. vertical focal distance divided by horizontal focal distance). This value is only taken into account if skewness is assumed to be zero and focal distance aspect ratio is marked as known, otherwise it is ignored. By default, this is 1.0, since it is taken into account that typically LCD sensor cells are square and hence aspect ratio focal distances is known and equal to 1. Notice that focal distance aspect ratio is not related to image size aspect ratio. Notice that a negative aspect ratio indicates that vertical axis is reversed. This can be useful in some situations where image vertical coordinates are reversed respect to the physical world (i.e. in computer graphics typically image vertical coordinates go downwards, while in physical world they go upwards).
      Parameters:
      focalDistanceAspectRatio - aspect ratio of focal distances to be set
      Throws:
      com.irurueta.geometry.estimators.LockedException - if estimator is locked.
      IllegalArgumentException - if focal distance aspect ratio is too close to zero, as it might produce numerical instabilities.

    • getListener

      public ImageOfAbsoluteConicRobustEstimatorListener 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(ImageOfAbsoluteConicRobustEstimatorListener listener) throws com.irurueta.geometry.estimators.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:
      com.irurueta.geometry.estimators.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 com.irurueta.geometry.estimators.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.
      com.irurueta.geometry.estimators.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 com.irurueta.geometry.estimators.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.
      com.irurueta.geometry.estimators.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 com.irurueta.geometry.estimators.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.
      com.irurueta.geometry.estimators.LockedException - if this estimator is locked because an estimation is being computed.

    • getHomographies

      public List<com.irurueta.geometry.Transformation2D> getHomographies()
      Gets list of homographies to estimate IAC.
      Returns:
      list of homographies to estimate IAC.

    • setHomographies

      public void setHomographies(List<com.irurueta.geometry.Transformation2D> homographies) throws com.irurueta.geometry.estimators.LockedException
      Sets list of homographies to estimate IAC.
      Parameters:
      homographies - list of homographies to estimate IAC.
      Throws:
      com.irurueta.geometry.estimators.LockedException - if estimator is locked.
      IllegalArgumentException - if provided list of homographies does not contain enough elements to estimate the DIAC using current settings.

    • getMinNumberOfRequiredHomographies

      public int getMinNumberOfRequiredHomographies()
      Returns minimum number of required homographies needed to estimate the Imag eof Absolute Conic (IAC). If no constraints are imposed, then at least 3 homographies are required. For each constraint imposed, one less equation will be required, hence if skewness is assumed to be known (by using its typical value of zero), then only 4 equations will be needed. If also the horizontal and vertical coordinates of the principal point are assumed to be known (by being placed at the 2D origin of coordinates, which is a typical value), then only 2 equations will be needed (1 homography).
      Returns:
      minimum number of required homographies required to estimate the IAC.

    • isReady

      public boolean isReady()
      Returns value indicating whether required data has been provided so that IAC estimation can start. If true, estimator is ready to compute the IAC, otherwise more data needs to be provided.
      Returns:
      true if estimator is ready, false otherwise.

    • getQualityScores

      public double[] getQualityScores()
      Returns quality scores corresponding to each homography. The larger the score value the better the quality of the homography. This implementation always returns null. Subclasses using quality scores must implement proper behaviour.
      Returns:
      quality scores corresponding to each homography.

    • setQualityScores

      public void setQualityScores(double[] qualityScores) throws com.irurueta.geometry.estimators.LockedException
      Sets quality scores corresponding to each homography. The larger the score value the better the quality of the homography. This implementation makes no action. Subclasses using quality scores must implement proper behaviour.
      Parameters:
      qualityScores - quality scores corresponding to each homography.
      Throws:
      com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress.
      IllegalArgumentException - if provided quality scores length is smaller than minimum required number of homographies.

    • estimate

      public abstract ImageOfAbsoluteConic estimate() throws com.irurueta.geometry.estimators.LockedException, com.irurueta.geometry.estimators.NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates Image of Absolute Conic (IAC).
      Returns:
      estimated IAC.
      Throws:
      com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress.
      com.irurueta.geometry.estimators.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.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create(com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an image of absolute conic robust estimator using provided method.
      Parameters:
      method - method of a robust estimator algorithm to estimate best IAC.
      Returns:
      an instance of an image of absolute conic robust estimator.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an image of absolute conic robust estimator using provided homographies.
      Parameters:
      homographies - list of homographies.
      qualityScores - quality scores corresponding to each homography.
      method - method of a robust estimator algorithm to estimate best IAC.
      Returns:
      an instance of an image of absolute conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of homographies and quality scores don't have the same size or size is too short.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create(List<com.irurueta.geometry.Transformation2D> homographies, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an image of absolute conic robust estimator using provided homographies.
      Parameters:
      homographies - list of homographies.
      method - method of a robust estimator algorithm to estimate best IAC.
      Returns:
      an instance of an image of absolute conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of homographies is too short.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create()
      Creates an image of absolute conic robust estimator using default method.
      Returns:
      an instance of an image of absolute conic robust estimator.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create(List<com.irurueta.geometry.Transformation2D> homographies, double[] qualityScores)
      Creates an image of absolute conic robust estimator using provided homographies.
      Parameters:
      homographies - list of homographies.
      qualityScores - quality scores corresponding to each point.
      Returns:
      an instance of an image of absolute conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of homographies and quality scores don't have the same size or size is too short.

    • create

      public static ImageOfAbsoluteConicRobustEstimator create(List<com.irurueta.geometry.Transformation2D> homographies)
      Creates an image of absolute conic robust estimator using provided homographies.
      Parameters:
      homographies - list of homographies.
      Returns:
      an instance of an image of absolute conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of homographies and is too short.

    • residual

      protected double residual(ImageOfAbsoluteConic iac, com.irurueta.geometry.Transformation2D homography)
      Computes the residual between an image of absolute conic (IAC) and a 2D transformation (homography). Residual is derived from the fact that rotation matrices are orthonormal (i.e. h1'*IAC*h2 = 0 and h1'*IAC*h1 = h2'*IAC*h2 --< h1'*IAC*h1 - h2'*IAC*h2 = 0). The residual will be the average error of those two equations.
      Parameters:
      iac - the matrix of an image of absolute conic (IAC)
      homography - 2D transformation (homography)
      Returns:
      residual.

    • internalSetHomographies

      private void internalSetHomographies(List<com.irurueta.geometry.Transformation2D> homographies)
      Sets list of homographies. This method does not check whether estimator is locked.
      Parameters:
      homographies - list of homographies to estimate IAC.
      Throws:
      IllegalArgumentException - if provided list of homographies is null or too small.