Fitting Superellipses

@article{Rosin2000FittingS,
  title={Fitting Superellipses},
  author={Paul L. Rosin},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
  year={2000},
  volume={22},
  pages={726-732}
}
  • Paul L. Rosin
  • Published 2000
  • Computer Science
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • In the literature, methods for fitting superellipses to data tend to be computationally expensive due to the nonlinear nature of the problem. This paper describes and tests several fitting techniques which provide different trade-offs between efficiency and accuracy. In addition, we describe various alternative error of fit measures that can be applied by most superellipse fitting methods. 
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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 22 REFERENCES
    Direct Least Square Fitting of Ellipses
    • 2,281
    • PDF
    Curve segmentation and representation by superellipses
    • 31
    • PDF
    Computational Geometry: An Introduction
    • 6,734
    Ellipse Fitting Using Orthogonal Hyperbolae and Stirling's Oval
    • 30
    • PDF
    A New One-Parametric Fitting Method for Planar Objects
    • 11
    Assessing Error of Fit Functions for Ellipses
    • 63
    • PDF
    Training PDMs on Models: The Case of Deformable Superellipses
    • 18
    • PDF
    Recovery of superquadric primitives from a range image using simulated annealing
    • 28
    A note on polygonal and elliptical approximation of mechanical parts
    • 71
    Error Of Fit Measures For Recovering Parametric Solids
    • 88
    • Highly Influential