Package com.irurueta.geometry.estimators

Class PROMedSDualQuadricRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.DualQuadricRobustEstimator
com.irurueta.geometry.estimators.PROMedSDualQuadricRobustEstimator
public class PROMedSDualQuadricRobustEstimator extends DualQuadricRobustEstimator
Finds the best quadric for provided collection of 3D planes using PROMedS algorithm.

  • Field Details

    • DEFAULT_STOP_THRESHOLD

      public static final double DEFAULT_STOP_THRESHOLD
      Default value to be used for stop threshold. Stop threshold can be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.
      See Also:

    • MIN_STOP_THRESHOLD

      public static final double MIN_STOP_THRESHOLD
      Minimum allowed stop threshold value.
      See Also:

    • stopThreshold

      private double stopThreshold
      Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

    • qualityScores

      private double[] qualityScores
      Quality scores corresponding to each 2D line. The larger the score value the better the quality of the sample.

  • Constructor Details

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator()
      Constructor.

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(List<Plane> planes)
      Constructor with planes.
      Parameters:
      planes - 3D planes to estimate a dual quadric.
      Throws:
      IllegalArgumentException - if provided list of planes don't have a size greater or equal than MINIMUM_SIZE.

    • PROMedSDualQuadricRobustEstimator

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

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(DualQuadricRobustEstimatorListener 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 dual quadric.
      Throws:
      IllegalArgumentException - if provided list of planes don't have a size greater or equal than MINIMUM_SIZE.

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(double[] qualityScores)
      Constructor.
      Parameters:
      qualityScores - quality scores corresponding to each provided plane.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 9 planes).

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(List<Plane> planes, double[] qualityScores)
      Constructor with planes.
      Parameters:
      planes - 3D planes to estimate a dual quadric.
      qualityScores - quality scores corresponding to each provided plane.
      Throws:
      IllegalArgumentException - if provided list of planes 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.

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(DualQuadricRobustEstimatorListener listener, double[] qualityScores)
      Constructor.
      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.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 9 planes).

    • PROMedSDualQuadricRobustEstimator

      public PROMedSDualQuadricRobustEstimator(DualQuadricRobustEstimatorListener listener, List<Plane> planes, double[] qualityScores)
      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 dual quadric.
      qualityScores - quality scores corresponding to each provided plane.
      Throws:
      IllegalArgumentException - if provided list of points 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.

  • Method Details

    • getStopThreshold

      public double getStopThreshold()
      Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. As in LMedS, the stop threshold can be used to prevent the PROMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.
      Returns:
      stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

    • setStopThreshold

      public void setStopThreshold(double stopThreshold) throws LockedException
      Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. As in LMedS, the stop threshold can be used to prevent the PROMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.
      Parameters:
      stopThreshold - stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.
      Throws:
      IllegalArgumentException - if provided value is zero or negative.
      LockedException - if robust estimator is locked because an estimation is already in progress.

    • getQualityScores

      public double[] getQualityScores()
      Returns quality scores corresponding to each provided plane. The larger the score value the better the quality of the sampled plane.
      Overrides:
      getQualityScores in class DualQuadricRobustEstimator
      Returns:
      quality scores corresponding to each point.

    • setQualityScores

      public void setQualityScores(double[] qualityScores) throws LockedException
      Sets quality scores corresponding to each provided plane. The larger the score value the better the quality of the sampled plane.
      Overrides:
      setQualityScores in class DualQuadricRobustEstimator
      Parameters:
      qualityScores - quality scores corresponding to each plane.
      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).

    • isReady

      public boolean isReady()
      Indicates if estimator is ready to start the quadric estimation. This is true when input data (i.e. 3D planes and quality scores) are provided and a minimum of MINIMUM_SIZE planes are available.
      Overrides:
      isReady in class DualQuadricRobustEstimator
      Returns:
      true if estimator is ready, false otherwise.

    • estimate

      public DualQuadric estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates a dual quadric using a robust estimator and the best set of 3D planes that fit into the locus of the estimated dual quadric found using the robust estimator.
      Specified by:
      estimate in class DualQuadricRobustEstimator
      Returns:
      a dual quadric.
      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 com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()
      Returns method being used for robust estimation.
      Specified by:
      getMethod in class DualQuadricRobustEstimator
      Returns:
      method being used for robust estimation.

    • internalSetQualityScores

      private void internalSetQualityScores(double[] qualityScores)
      Sets quality scores corresponding to each provided plane. This method is used internally and does not check whether instance is locked or not.
      Parameters:
      qualityScores - quality scores to be set.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE.