Package com.irurueta.geometry.estimators

Class DualConicRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.DualConicRobustEstimator
Direct Known Subclasses:
LMedSDualConicRobustEstimator, MSACDualConicRobustEstimator, PROMedSDualConicRobustEstimator, PROSACDualConicRobustEstimator, RANSACDualConicRobustEstimator
public abstract class DualConicRobustEstimator extends Object
This is an abstract class for algorithms to robustly find the best dual conic that fits in a collection of 2D lines. Implementations of this class should be able to detect and discard outliers in order to find the best solution.

  • Field Details

    • MINIMUM_SIZE

      public static final int MINIMUM_SIZE
      Minimum number of 2D lines required to estimate a Dual Conic.
      See Also:

    • 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:

    • DEFAULT_ROBUST_METHOD

      public static final com.irurueta.numerical.robust.RobustEstimatorMethod DEFAULT_ROBUST_METHOD
      Default robust estimator method when none is provided.

    • listener

      protected DualConicRobustEstimatorListener 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.

    • lines

      protected List<Line2D> lines
      List of lines to be used to estimate a dual conic. Provided list must have a size greater or equal than MINIMUM_SIZE.

    • testLine

      private com.irurueta.algebra.Matrix testLine
      Matrix representation of a 2D line to be reused when computing residuals.

    • testDualC

      private com.irurueta.algebra.Matrix testDualC
      Matrix representation of a dual conic to be reused when computing residuals.

  • Constructor Details

    • DualConicRobustEstimator

      protected DualConicRobustEstimator()
      Constructor.

    • DualConicRobustEstimator

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

    • DualConicRobustEstimator

      protected DualConicRobustEstimator(List<Line2D> lines)
      Constructor with lines.
      Parameters:
      lines - 2D lines to estimate a dual conic.
      Throws:
      IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.

    • DualConicRobustEstimator

      protected DualConicRobustEstimator(DualConicRobustEstimatorListener listener, List<Line2D> lines)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      lines - 2D lines to estimate a dual conic.
      Throws:
      IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.

  • Method Details

    • getListener

      public DualConicRobustEstimatorListener 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(DualConicRobustEstimatorListener 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 that 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.

    • getLines

      public List<Line2D> getLines()
      Returns list of lines to be used to estimate a dual conic. Provided list have a size greater or equal than MINIMUM_SIZE.
      Returns:
      list of lines to be used to estimate a dual conic.

    • setLines

      public void setLines(List<Line2D> lines) throws LockedException
      Sets list of lines to be used to estimate a dual conic. Provided list must have a size greater or equal than MINIMUM_SIZE.
      Parameters:
      lines - list of lines to be used to estimate a dual conic.
      Throws:
      IllegalArgumentException - if provided list of lines 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 dual conic estimation. This is true when 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 return null. Subclasses using quality scores must implement proper behaviour.
      Returns:
      quality scores corresponding to each line.

    • 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 matching. This implementation makes no action. Subclasses using quality scores must implement proper behaviour.
      Parameters:
      qualityScores - quality scores corresponding to each 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. 9 samples).

    • create

      public static DualConicRobustEstimator create(com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line samples and using provided robust estimator method.
      Parameters:
      method - method of a robust estimator algorithm to estimate bes dual conic.
      Returns:
      an instance of a dual conic robust estimator.

    • create

      public static DualConicRobustEstimator create(List<Line2D> lines, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line samples and using provided lines and robust estimator method.
      Parameters:
      lines - 2D lines to estimate a dual conic.
      method - method of a robust estimator algorithm to estimate the best dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line 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 dual conic.
      Returns:
      an instance of a dual conic robust estimator.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, List<Line2D> lines, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line samples and using provided listener and lines.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      lines - 2D lines to estimate a dual conic.
      method - method of a robust estimator algorithm to estimate the best dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of lines don't have a size greater or equal than MINIMUM_SIZE.

    • create

      public static DualConicRobustEstimator create(double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line samples and using provided robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each provided line.
      method - method of a robust estimator algorithm to estimate bes dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 5 lines).

    • create

      public static DualConicRobustEstimator create(List<Line2D> lines, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator method based on 2D line samples and using provided lines and robust estimator method.
      Parameters:
      lines - 2D lines to estimate a dual conic.
      qualityScores - quality scores corresponding to each provided line.
      method - method of a robust estimator algorithm to estimate the best dual conic.
      Returns:
      an instance of a dual conic 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.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line 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 line.
      method - method of a robust estimator algorithm to estimate the best dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 5 lines).

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, List<Line2D> lines, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates a dual conic robust estimator based on 2D line samples and using provided listener and lines.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      lines - 2D lines to estimate a dual conic.
      qualityScores - quality scores corresponding to each provided line.
      method - method of a robust estimator algorithm to estimate the best dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of lines don'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 DualConicRobustEstimator create()
      Creates a dual conic robust estimator based on 2D line samples and using default robust estimator method.
      Returns:
      an instance of a dual conic robust estimator.

    • create

      public static DualConicRobustEstimator create(List<Line2D> lines)
      Creates a dual conic robust estimator based on 2D line samples and using provided lines and default robust estimator method.
      Parameters:
      lines - 2D lines to estimate a dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of lines doesn't have a size greater or equal than MINIMUM_SIZE.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener)
      Creates a dual conic robust estimator based on 2D line 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 dual conic robust estimator.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, List<Line2D> lines)
      Creates a dual conic robust estimator based on 2D line samples and using provided listener and lines and default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      lines - 2D lines to estimate a dual conic.
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided list of lines doesn't have a size greater or equal than MINIMUM_SIZE.

    • create

      public static DualConicRobustEstimator create(double[] qualityScores)
      Creates a dual conic robust estimator based on 2D line samples and using default robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each provided line
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 5 lines).

    • create

      public static DualConicRobustEstimator create(List<Line2D> lines, double[] qualityScores)
      Creates a dual conic robust estimator based on 2D line samples and using provided lines and default estimator method.
      Parameters:
      lines - 2D lines to estimate a dual conic.
      qualityScores - quality scores corresponding to each provided line
      Returns:
      an instance of a dual conic 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.

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, double[] qualityScores)
      Creates a dual conic robust estimator based on 2D line 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 line
      Returns:
      an instance of a dual conic robust estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 5 lines).

    • create

      public static DualConicRobustEstimator create(DualConicRobustEstimatorListener listener, List<Line2D> lines, double[] qualityScores)
      Creates a dual conic robust estimator based on 2D line samples and using provided listener and lines and default estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      lines - 2D lines to estimate a dual conic.
      qualityScores - quality scores corresponding to each provided line
      Returns:
      an instance of a dual conic 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 DualConic estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates a dual conic using a robust estimator and the best set of 2D lines that fit into the locus of the estimated dual conic found using the robust estimator.
      Returns:
      a dual conic.
      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.

    • internalSetLines

      private void internalSetLines(List<Line2D> lines)
      Internal method to set list of lines to be used to estimate a dual conic. This method does not check whether estimator is locked or not.
      Parameters:
      lines - list of lines to be used to estimate a dual conic.
      Throws:
      IllegalArgumentException - if provided list of lines doesn't have a size greater or equal than MINIMUM_SIZE.

    • residual

      protected double residual(DualConic dc, Line2D line)
      Computes the residual between a dual conic and a 2D line.
      Parameters:
      dc - a dual conic.
      line - a 2D line.
      Returns:
      residual.