Package com.irurueta.geometry.estimators

Class PROSACEuclideanTransformation2DRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.EuclideanTransformation2DRobustEstimator
com.irurueta.geometry.estimators.PROSACEuclideanTransformation2DRobustEstimator
public class PROSACEuclideanTransformation2DRobustEstimator extends EuclideanTransformation2DRobustEstimator
Finds the best Euclidean 2D transformation for provided collections of matched 2D points using PROSAC algorithm.

  • Field Details

    • DEFAULT_THRESHOLD

      public static final double DEFAULT_THRESHOLD
      Constant defining default threshold to determine whether points are inliers or not. By default, 1.0 is considered a good value for cases where measures are done on pixels, since typically the minimum resolution is 1 pixel.
      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 points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. distance) a possible solution has on a matched pair of points.

    • qualityScores

      private double[] qualityScores
      Quality scores corresponding to each pair of matched points. 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

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator()
      Constructor.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points 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:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points 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 stars, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(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).

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points 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:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      Throws:
      IllegalArgumentException - if provided lists of points and array of quality scores don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener 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 points.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points 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 stars, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an affine 2D transformation.
      outputPoints - list of output points to be used to estimate an affine 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points 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:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points 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 stars, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(double[] qualityScores, boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points 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:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided lists of points and array of quality scores don't have the same size or their size is smaller than MINIMUM_SIZE.

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, double[] qualityScores, boolean weakMinimumSizeAllowed)
      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 points.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • PROSACEuclideanTransformation2DRobustEstimator

      public PROSACEuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points 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 stars, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an affine 2D transformation.
      outputPoints - list of output points to be used to estimate an affine 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.
      Throws:
      IllegalArgumentException - if provided lists of points 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 points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. Euclidean distance) a possible solution has on a matched pair of points.
      Returns:
      threshold to determine whether points are inliers or not when testing possible estimation solutions.

    • setThreshold

      public void setThreshold(double threshold) throws LockedException
      Sets threshold to determine whether points are inliers or not when testing possible estimation solutions. The threshold refers to the amount of error (i.e. Euclidean distance) a possible solution has on a matched pair of points.
      Parameters:
      threshold - threshold to determine whether points are inliers or not when testing possible estimation solutions.
      Throws:
      IllegalArgumentException - if provided values 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 points. The larger the score value the better the quality of the matching.
      Overrides:
      getQualityScores in class EuclideanTransformation2DRobustEstimator
      Returns:
      quality scores corresponding to each pair of matched points.

    • setQualityScores

      public void setQualityScores(double[] qualityScores) throws LockedException
      Sets quality scores corresponding to each pair of matched points. The larger the score value the better the quality of the matching.
      Overrides:
      setQualityScores in class EuclideanTransformation2DRobustEstimator
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      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 Euclidean 2D transformation estimation. This is true when input data (i.e. lists of matched points and quality scores) are provided and a minimum of MINIMUM_SIZE points are available.
      Overrides:
      isReady in class EuclideanTransformation2DRobustEstimator
      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 EuclideanTransformation2D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates an Euclidean 2D transformation using a robust estimator and the best set of matched 2D point correspondences found using the robust estimator.
      Specified by:
      estimate in class EuclideanTransformation2DRobustEstimator
      Returns:
      an Euclidean 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 EuclideanTransformation2DRobustEstimator
      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 EuclideanTransformation2DRobustEstimator
      Returns:
      standard deviation used for refinement.

    • internalSetQualityScores

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