A physics-based framework for segmentation, shape and motion estimation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper summarizes our research efforts towards the development of a physics-based modeling framework that addresses the difficult problems of segmentation, shape and motion estimation in a uniform way. The framework is based on the sophisticated integration of mathematical techniques from geometry, physics and mechanics, with special emphasis on the design of algorithms with close to real-time performance. We demonstrate the usefulness of this framework in experiments involving image and range data, as well as in biomedical applications.

Original languageEnglish (US)
Title of host publicationObject Representation in Computer Vision - International NSF-ARPA Workshop, Proceedings
EditorsAri Gross, Martial Hebert, Terry Boult, Jean Ponce
PublisherSpringer Verlag
Pages233-247
Number of pages15
ISBN (Print)3540604774, 9783540604778
DOIs
StatePublished - 1995
Externally publishedYes
EventInternational NSF-ARPA Workshop on Object Representation in Computer Vision, 1994 - New York City, United States
Duration: Dec 5 1994Dec 7 1994

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume994
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational NSF-ARPA Workshop on Object Representation in Computer Vision, 1994
Country/TerritoryUnited States
CityNew York City
Period12/5/9412/7/94

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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