Package com.irurueta.geometry.estimators

Class MSACEuclideanTransformation3DRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.EuclideanTransformation3DRobustEstimator
com.irurueta.geometry.estimators.MSACEuclideanTransformation3DRobustEstimator
public class MSACEuclideanTransformation3DRobustEstimator extends EuclideanTransformation3DRobustEstimator
Finds the best Euclidean 3D transformation for provided collections of matched 3D points using MSAC 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:

    • 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.

  • Constructor Details

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator()
      Constructor.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(List<Point3D> inputPoints, List<Point3D> outputPoints)
      Constructor with lists of points to be used to estimate an Euclidean 3D 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 ot be used to estimate an Euclidean 3D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 3D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(EuclideanTransformation3DRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(EuclideanTransformation3DRobustEstimatorListener listener, List<Point3D> inputPoints, List<Point3D> outputPoints)
      Constructor with listener and lists of points to be used to estimate an Euclidean 3D 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 starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 3D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 3D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      weakMinimumSizeAllowed - true allows 3 points, false requires 4.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(List<Point3D> inputPoints, List<Point3D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with lists of points to be used to estimate an Euclidean 3D 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 ot be used to estimate an Euclidean 3D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 3D 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.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(EuclideanTransformation3DRobustEstimatorListener 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.

    • MSACEuclideanTransformation3DRobustEstimator

      public MSACEuclideanTransformation3DRobustEstimator(EuclideanTransformation3DRobustEstimatorListener listener, List<Point3D> inputPoints, List<Point3D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with listener and lists of points to be used to estimate an Euclidean 3D 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 starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 3D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 3D 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.

  • 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.
      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 EuclideanTransformation3D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates an Euclidean 3D transformation using a robust estimator and the best set of matched 3D point correspondences found using the robust estimator.
      Specified by:
      estimate in class EuclideanTransformation3DRobustEstimator
      Returns:
      an Euclidean 3D 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 EuclideanTransformation3DRobustEstimator
      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 EuclideanTransformation3DRobustEstimator
      Returns:
      standard deviation used for refinement.