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Physics in a fantasy world vs robust statistical estimation

  • Terrance E. Boult
  • Samuel D. Fenster
  • Thomas O'Donnell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 994)

Abstract

Deformable models in the “physically-based” paradigm are almost always formulated in an ad-hoc fashion, not related to physical reality — they apply the equations on physics in a fantasy world. This paper discusses some of the drawbacks of this approach. Still these techniques have shown themselves to be useful, so there must be something here. This paper reinterprets these “physics-based” techniques by putting them into a framework of robust statistics. We use this framework to analyze the problems and ad-hoc solutions found in common physically-based formulations. These include incorrect prior shape models; bad relative weights of various energies; and the two-stage approach to minimization (adjusting global, then local shape parameters). We examine the statistical implications of common deformable object formulations. In our reformulation, the units are meaningful, training data plays a fundamental role, different kinds of information may be fused, and certainties can be reported for the segmentation results. The robust aspects of the reformulation are necessary to combat interference from the necessarily large amount of unmodeled image information.

Keywords

Mahalanobis Distance IEEE Conf Data Force Deformable Model Image Force 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Terrance E. Boult
    • 1
  • Samuel D. Fenster
    • 2
  • Thomas O'Donnell
    • 2
  1. 1.EECS Dept., 304 Packard LaboratoryLehigh UniversityBethlehemUSA
  2. 2.Dept. of Computer ScienceColumbia Univ.NYCUSA

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