Class Point3DRefiner<T extends Point3D>

Type Parameters:
T - an implementation of a 3D point.
Direct Known Subclasses:
HomogeneousPoint3DRefiner, InhomogeneousPoint3DRefiner

public abstract class Point3DRefiner<T extends Point3D> extends SamplesAndInliersDataRefiner<T,Plane>
Refines a 3D point by taking into account an initial estimation, inlier samples and their residuals. This class can be used to find a solution that minimizes error of inliers in LMSE terms. Typically, a refiner is used by a robust estimator, however it can also be useful in some other situations.
  • Field Details

    • refinementStandardDeviation

      private double refinementStandardDeviation
      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.
  • Constructor Details

    • Point3DRefiner

      protected Point3DRefiner()
      Constructor.
    • Point3DRefiner

      protected Point3DRefiner(T initialEstimation, boolean keepCovariance, BitSet inliers, double[] residuals, int numInliers, List<Plane> samples, double refinementStandardDeviation)
      Constructor.
      Parameters:
      initialEstimation - initial estimation to be set.
      keepCovariance - true if covariance of estimation must be kept after refinement, false otherwise.
      inliers - set indicating which of the provided matches are inliers.
      residuals - residuals for matched samples.
      numInliers - number of inliers on initial estimation.
      samples - collection of samples.
      refinementStandardDeviation - standard deviation used for Levenberg-Marquardt fitting.
    • Point3DRefiner

      protected Point3DRefiner(T initialEstimation, boolean keepCovariance, com.irurueta.numerical.robust.InliersData inliersData, List<Plane> samples, double refinementStandardDeviation)
      Constructor.
      Parameters:
      initialEstimation - initial estimation to be set.
      keepCovariance - true if covariance of estimation must be kept after refinement, false otherwise.
      inliersData - inlier data, typically obtained from a robust estimator.
      samples - collection of samples.
      refinementStandardDeviation - standard deviation used for Levenberg-Marquardt fitting.
  • Method Details

    • getRefinementStandardDeviation

      public 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.
      Returns:
      standard deviation used for refinement.
    • setRefinementStandardDeviation

      public void setRefinementStandardDeviation(double refinementStandardDeviation) throws LockedException
      Sets 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.
      Parameters:
      refinementStandardDeviation - standard deviation used for refinement.
      Throws:
      LockedException - if estimator is locked.
    • residual

      protected double residual(Point3D point, Plane plane)
      Computes the residual between a point and a plane as their distance.
      Parameters:
      point - a point.
      plane - a plane.
      Returns:
      residual (distance between provided point and plane).
    • totalResidual

      protected double totalResidual(Point3D point)
      Computes total residual among all provided inlier samples.
      Parameters:
      point - a point.
      Returns:
      total residual.