Package com.irurueta.geometry.estimators

Class PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.ProjectiveTransformation2DRobustEstimator
com.irurueta.geometry.estimators.LineCorrespondenceProjectiveTransformation2DRobustEstimator
com.irurueta.geometry.estimators.PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator
public class PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator extends LineCorrespondenceProjectiveTransformation2DRobustEstimator
Finds the best projective 2D transformation for provided collections of matched 2D lines using PROSAC 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:

    • DEFAULT_COMPUTE_AND_KEEP_INLIERS

      public static final boolean DEFAULT_COMPUTE_AND_KEEP_INLIERS
      Indicates that by default inliers will only be computed but not kept.
      See Also:

    • DEFAULT_COMPUTE_AND_KEEP_RESIDUALS

      public static final boolean DEFAULT_COMPUTE_AND_KEEP_RESIDUALS
      Indicates that by default residuals will only be computed but not kept.
      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.

    • qualityScores

      private double[] qualityScores
      Quality scores corresponding to each pair of matched lines. The larger the score value the better the quality of the matching.

    • computeAndKeepInliers

      private boolean computeAndKeepInliers
      Indicates whether inliers must be computed and kept.

    • computeAndKeepResiduals

      private boolean computeAndKeepResiduals
      Indicates whether residuals must be computed and kept.

  • Constructor Details

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator()
      Constructor.

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(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.

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(ProjectiveTransformation2DRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(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.

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(double[] qualityScores)
      Constructor.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(List<Line2D> inputLines, List<Line2D> outputLines, double[] qualityScores)
      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.
      qualityScores - quality scores corresponding to each pair of matched lines.
      Throws:
      IllegalArgumentException - if provided lists of lines and array of quality scores don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(ProjectiveTransformation2DRobustEstimatorListener 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 pair of matched lines.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator

      public PROSACLineCorrespondenceProjectiveTransformation2DRobustEstimator(ProjectiveTransformation2DRobustEstimatorListener listener, List<Line2D> inputLines, List<Line2D> outputLines, double[] qualityScores)
      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.
      qualityScores - quality scores corresponding to each pair of matched lines.
      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.

    • getQualityScores

      public double[] getQualityScores()
      Returns quality scores corresponding to each pair of matched lines. The larger the score value the better the quality of the matching.
      Overrides:
      getQualityScores in class LineCorrespondenceProjectiveTransformation2DRobustEstimator
      Returns:
      quality scores corresponding to each pair of matched lines.

    • setQualityScores

      public void setQualityScores(double[] qualityScores) throws LockedException
      Sets quality scores corresponding to each pair of matched lines. The larger the score value the better the quality of the matching.
      Overrides:
      setQualityScores in class LineCorrespondenceProjectiveTransformation2DRobustEstimator
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched lines.
      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. 3 samples).

    • isReady

      public boolean isReady()
      Indicates if estimator is ready to start the projective 2D transformation estimation. This is true when input data (i.e. lists of matched lines and quality scores) are provided and a minimum of MINIMUM_SIZE lines are available.
      Overrides:
      isReady in class LineCorrespondenceProjectiveTransformation2DRobustEstimator
      Returns:
      true if estimator is ready, false otherwise.

    • isComputeAndKeepInliersEnabled

      public boolean isComputeAndKeepInliersEnabled()
      Indicates whether inliers must be computed and kept.
      Returns:
      true if inliers must be computed and kept, false if inliers only need to be computed but not kept.

    • setComputeAndKeepInliersEnabled

      public void setComputeAndKeepInliersEnabled(boolean computeAndKeepInliers) throws LockedException
      Specifies whether inliers must be computed and kept.
      Parameters:
      computeAndKeepInliers - true if inliers must be computed and kept, false if inliers only need to be computed but not kept.
      Throws:
      LockedException - if estimator is locked.

    • isComputeAndKeepResidualsEnabled

      public boolean isComputeAndKeepResidualsEnabled()
      Indicates whether residuals must be computed and kept.
      Returns:
      true if residuals must be computed and kept, false if residuals only need to be computed but not kept.

    • setComputeAndKeepResidualsEnabled

      public void setComputeAndKeepResidualsEnabled(boolean computeAndKeepResiduals) throws LockedException
      Specifies whether residuals must be computed and kept.
      Parameters:
      computeAndKeepResiduals - true if residuals must be computed and kept, false if residuals only need to be computed but not kept.
      Throws:
      LockedException - if estimator is locked.

    • 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.

    • internalSetQualityScores

      private void internalSetQualityScores(double[] qualityScores)
      Sets quality scores corresponding to each pair of matched lines. 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.