Package com.irurueta.ar.calibration.estimators

Class LMedSRadialDistortionRobustEstimator

java.lang.Object
com.irurueta.ar.calibration.estimators.RadialDistortionRobustEstimator
com.irurueta.ar.calibration.estimators.LMedSRadialDistortionRobustEstimator
public class LMedSRadialDistortionRobustEstimator extends RadialDistortionRobustEstimator
Finds the best radial distortion for provided collection of 2D points using LMedS 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.

  • Constructor Details

    • LMedSRadialDistortionRobustEstimator

      public LMedSRadialDistortionRobustEstimator()
      Constructor.

    • LMedSRadialDistortionRobustEstimator

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

    • LMedSRadialDistortionRobustEstimator

      public LMedSRadialDistortionRobustEstimator(List<com.irurueta.geometry.Point2D> distortedPoints, List<com.irurueta.geometry.Point2D> undistortedPoints)
      Constructor.
      Parameters:
      distortedPoints - list of distorted points. Distorted points are obtained after radial distortion is applied to an undistorted point.
      undistortedPoints - list of undistorted points.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MIN_NUMBER_OF_POINTS.

    • LMedSRadialDistortionRobustEstimator

      public LMedSRadialDistortionRobustEstimator(List<com.irurueta.geometry.Point2D> distortedPoints, List<com.irurueta.geometry.Point2D> undistortedPoints, RadialDistortionRobustEstimatorListener listener)
      Constructor.
      Parameters:
      distortedPoints - list of distorted points. Distorted points are obtained after radial distortion is applied to an undistorted point.
      undistortedPoints - list of undistorted points.
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MIN_NUMBER_OF_POINTS.

    • LMedSRadialDistortionRobustEstimator

      public LMedSRadialDistortionRobustEstimator(List<com.irurueta.geometry.Point2D> distortedPoints, List<com.irurueta.geometry.Point2D> undistortedPoints, com.irurueta.geometry.Point2D distortionCenter)
      Constructor.
      Parameters:
      distortedPoints - list of distorted points. Distorted points are obtained after radial distortion is applied to an undistorted point.
      undistortedPoints - list of undistorted points.
      distortionCenter - radial distortion center. If null it is assumed to be the origin of coordinates, otherwise this is typically equal to the camera principal point.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MIN_NUMBER_OF_POINTS.

    • LMedSRadialDistortionRobustEstimator

      public LMedSRadialDistortionRobustEstimator(List<com.irurueta.geometry.Point2D> distortedPoints, List<com.irurueta.geometry.Point2D> undistortedPoints, com.irurueta.geometry.Point2D distortionCenter, RadialDistortionRobustEstimatorListener listener)
      Constructor.
      Parameters:
      distortedPoints - list of distorted points. Distorted points are obtained after radial distortion is applied to an undistorted point.
      undistortedPoints - list of undistorted points.
      distortionCenter - radial distortion center. If null it is assumed to be the origin of coordinates, otherwise this is typically equal to the camera principal point.
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MIN_NUMBER_OF_POINTS.

  • 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. 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.
      Returns:
      stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.

    • setStopThreshold

      public void setStopThreshold(double stopThreshold) throws com.irurueta.geometry.estimators.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. 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.
      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.
      com.irurueta.geometry.estimators.LockedException - if robust estimator is locked because an estimation is already in progress.

    • estimate

      public RadialDistortion estimate() throws com.irurueta.geometry.estimators.LockedException, com.irurueta.geometry.estimators.NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates a radial distortion using a robust estimator and the best set of matched 2D points found using the robust estimator.
      Specified by:
      estimate in class RadialDistortionRobustEstimator
      Returns:
      a radial distortion.
      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 com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()
      Returns method being used for robust estimation
      Specified by:
      getMethod in class RadialDistortionRobustEstimator
      Returns:
      method being used for robust estimation