Package com.irurueta.ar.calibration.estimators

Class LMedSDualAbsoluteQuadricRobustEstimator

java.lang.Object
com.irurueta.ar.calibration.estimators.DualAbsoluteQuadricRobustEstimator
com.irurueta.ar.calibration.estimators.LMedSDualAbsoluteQuadricRobustEstimator
public class LMedSDualAbsoluteQuadricRobustEstimator extends DualAbsoluteQuadricRobustEstimator
Finds the best Dual Absolute Quadric (DAQ) for provided collection of cameras 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 the equations used to estimate the DAQ depending on the required settings (zero skewness, principal point at origin, and known aspect ratio).
      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 one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.

  • Constructor Details

    • LMedSDualAbsoluteQuadricRobustEstimator

      public LMedSDualAbsoluteQuadricRobustEstimator()
      Constructor.

    • LMedSDualAbsoluteQuadricRobustEstimator

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

    • LMedSDualAbsoluteQuadricRobustEstimator

      public LMedSDualAbsoluteQuadricRobustEstimator(List<com.irurueta.geometry.PinholeCamera> cameras)
      Constructor.
      Parameters:
      cameras - list of cameras used to estimate the Dual Absolute Quadric (DAQ), which can be used to obtain pinhole camera intrinsic parameters.
      Throws:
      IllegalArgumentException - if not enough cameras are provided for default settings. Hence, at least 2 cameras must be provided.

    • LMedSDualAbsoluteQuadricRobustEstimator

      public LMedSDualAbsoluteQuadricRobustEstimator(List<com.irurueta.geometry.PinholeCamera> cameras, DualAbsoluteQuadricRobustEstimatorListener listener)
      Constructor.
      Parameters:
      cameras - list of cameras used to estimate the Dual AbsoluteQuadric (DAQ), which can be used to obtain pinhole camera intrinsic parameters.
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Throws:
      IllegalArgumentException - if not enough cameras are provided for default settings. Hence, at least 2 cameras 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 tat if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value lower than the one typically used in RANSAC, and yet the algorithm 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 DualAbsoluteQuadric estimate() throws com.irurueta.geometry.estimators.LockedException, com.irurueta.geometry.estimators.NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates the Dual Absolute Quadric using provided cameras.
      Specified by:
      estimate in class DualAbsoluteQuadricRobustEstimator
      Returns:
      estimated Dual Absolute Quadric (DAQ).
      Throws:
      com.irurueta.geometry.estimators.LockedException - if robust estimator is locked.
      com.irurueta.geometry.estimators.NotReadyException - if no valid input data has already been provided.
      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 DualAbsoluteQuadricRobustEstimator
      Returns:
      method being used for robust estimation.