Class MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator


public class MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator extends LineCorrespondenceProjectiveTransformation2DRobustEstimator
Finds the best projective 2D transformation for provided collections of matched 2D lines using MSAC algorithm.
  • Field Details

    • DEFAULT_THRESHOLD

      public static final double DEFAULT_THRESHOLD
      Constant defining default threshold to determine whether lines are inliers or not. Residuals to determine whether lines are inliers or not are computed by comparing two lines algebraically (e.g. doing the dot product of their parameters). A residual of 0 indicates that dot product was 1 or -1 and lines were equal. A residual of 1 indicates that dot product was 0 and lines were orthogonal. If dot product between lines is -1, then although their director vectors are opposed, lines are considered equal, since sign changes are not taken into account and their residuals will be 0.
      See Also:
    • MIN_THRESHOLD

      public static final double MIN_THRESHOLD
      Minimum value that can be set as threshold. Threshold must be strictly greater than 0.0.
      See Also:
    • threshold

      private double threshold
      Threshold to determine whether lines are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. distance and director vector angle difference) a possible solution has on a matched pair of lines.
  • Constructor Details

    • MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator()
      Constructor.
    • MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(List<Line2D> inputLines, List<Line2D> outputLines)
      Constructor with lists of lines to be used to estimate a projective 2D transformation. Lines in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      inputLines - list of input lines to be used to estimate a projective 2D transformation.
      outputLines - list of output lines to be used to estimate a projective 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of lines don't have the same size or their size is smaller than MINIMUM_SIZE.
    • MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(ProjectiveTransformation2DRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
    • MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public MSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(ProjectiveTransformation2DRobustEstimatorListener listener, List<Line2D> inputLines, List<Line2D> outputLines)
      Constructor with listener and lists of lines to be used to estimate a projective 2D transformation. Lines in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputLines - list of input lines to be used to estimate a projective 2D transformation.
      outputLines - list of output lines to be used to estimate a projective 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of lines don't have the same size or their size is smaller than MINIMUM_SIZE.
  • Method Details

    • getThreshold

      public double getThreshold()
      Returns threshold to determine whether lines are inliers or not when testing possible estimation solutions. Residuals to determine whether lines are inliers or not are computed by comparing two lines algebraically (e.g. doing the dot product of their parameters). A residual of 0 indicates that dot product was 1 or -1 and lines were equal. A residual of 1 indicates that dot product was 0 and lines were orthogonal. If dot product between lines is -1, then although their director vectors are opposed, lines are considered equal, since sign changes are not taken into account and their residuals will be 0.
      Returns:
      threshold to determine whether matched lines are inliers or not.
    • setThreshold

      public void setThreshold(double threshold) throws LockedException
      Sets threshold to determine whether lines are inliers or not when testing possible estimation solutions. Residuals to determine whether lines are inliers or not are computed by comparing two lines algebraically (e.g. doing the dot product of their parameters). A residual of 0 indicates that dot product was 1 or -1 and lines were equal. A residual of 1 indicates that dot product was 0 and lines were orthogonal. If dot product between lines is -1, then although their director vectors are opposed, lines are considered equal, since sign changes are not taken into account and their residuals will be 0.
      Parameters:
      threshold - threshold to determine whether matched lines are inliers or not.
      Throws:
      IllegalArgumentException - if provided value is equal or less than zero.
      LockedException - if robust estimator is locked because an estimation is already in progress.
    • estimate

      public ProjectiveTransformation2D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates a projective 2D transformation using a robust estimator and the best set of matched 2D lines correspondences found using the robust estimator.
      Specified by:
      estimate in class ProjectiveTransformation2DRobustEstimator
      Returns:
      a projective 2D transformation.
      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 ProjectiveTransformation2DRobustEstimator
      Returns:
      method being used for robust estimation.
    • getRefinementStandardDeviation

      protected double getRefinementStandardDeviation()
      Gets standard deviation used for Levenberg-Marquardt fitting during refinement. Returned value gives an indication of how much variance each residual has. Typically, this value is related to the threshold used on each robust estimation, since residuals of found inliers are within the range of such threshold.
      Specified by:
      getRefinementStandardDeviation in class ProjectiveTransformation2DRobustEstimator
      Returns:
      standard deviation used for refinement.