Body plans

Research output: Contribution to journalConference article

Abstract

This paper describes a representation for people and animals, called a body plan, which is adapted to segmentation and to recognition in complex environments. The representation is an organized collection of grouping hints obtained from a combination of constraints on color and texture and constraints on geometric properties such as the structure of individual parts and the relationships between parts. Body plans can be learned from image data, using established statistical learning techniques. The approach is illustrated with two examples of programs that successfully use body plans for recognition: one example involves determining whether a picture contains a scantily clad human, using a body plan built by hand; the other involves determining whether a picture contains a horse, using a body plan learned from image data. In both cases, the system demonstrates excellent performance on large, uncontrolled test sets and very large and diverse control sets.

Original languageEnglish (US)
Pages (from-to)678-683
Number of pages6
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
StatePublished - Jan 1 1997
Externally publishedYes
EventProceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - San Juan, PR, USA
Duration: Jun 17 1997Jun 19 1997

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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