Package com.irurueta.ar.calibration.estimators

Class LMedSImageOfAbsoluteConicRobustEstimator

java.lang.Object
com.irurueta.ar.calibration.estimators.ImageOfAbsoluteConicRobustEstimator
com.irurueta.ar.calibration.estimators.LMedSImageOfAbsoluteConicRobustEstimator
public class LMedSImageOfAbsoluteConicRobustEstimator extends ImageOfAbsoluteConicRobustEstimator
Finds the best Image of AbsoluteConic (IAC) for provided collection of homographies (2D transformations) 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. Threshold is defined by equations h1'*IAC*h2 = 0 and h1'*IAC*h1 = h2'*IAC*h2 --< h1'*IAC*h1 - h2'*IAC*h2 = 0, where h1 and h2 are the 1st and 2nd columns of an homography (2D transformation). These equations are derived from the fact that rotation matrices are orthonormal.
      See Also:

    • MIN_STOP_THRESHOLD

      public static final double MIN_STOP_THRESHOLD
      Minimum value that can be set as stop threshold. Threshold must be strictly greater than 0.0.
      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

    • LMedSImageOfAbsoluteConicRobustEstimator

      public LMedSImageOfAbsoluteConicRobustEstimator()
      Constructor.

    • LMedSImageOfAbsoluteConicRobustEstimator

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

    • LMedSImageOfAbsoluteConicRobustEstimator

      public LMedSImageOfAbsoluteConicRobustEstimator(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.

    • LMedSImageOfAbsoluteConicRobustEstimator

      public LMedSImageOfAbsoluteConicRobustEstimator(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

    • 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 ImageOfAbsoluteConic estimate() throws com.irurueta.geometry.estimators.LockedException, com.irurueta.geometry.estimators.NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates Image of Absolute Conic (IAC).
      Specified by:
      estimate in class ImageOfAbsoluteConicRobustEstimator
      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 com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()
      Returns method being used for robust estimation
      Specified by:
      getMethod in class ImageOfAbsoluteConicRobustEstimator
      Returns:
      method being used for robust estimation