Determining articulated motion from perspective views: A decomposition approach

Robert J. Holt, Thomas S. Huang, Arun N. Netravali, Richard J. Qian

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the problem of estimating the 3D motion of an articulated object, such as a robot arm or a human body, from a monocular sequence of 2D perspective views. We advocate an approach of decomposition. The object under analysis is decomposed into simpler parts, each containing a small number of links. We first estimate the motion of the simplest part(s) and then propagate the analysis to the remaining parts of the object. Human gait is used as an example; however, the approach is general. To use this decomposition approach, we need a repertoire of results for the motion of simple articulated objects: motion estimation algorithms, uniqueness and number of solutions (especially, how many views are needed for uniqueness). With the help of techniques in algebraic geometry, we have results for a number of cases which are particularly useful for human gait analysis. Published by Elsevier Science Ltd.

Original languageEnglish (US)
Pages (from-to)1435-1449
Number of pages15
JournalPattern Recognition
Volume30
Issue number9
DOIs
StatePublished - Sep 1997

Keywords

  • Algebraic geometry
  • Articulated objects
  • Decomposition
  • Image sequences
  • Motion estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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