Finding objects by grouping primitives

David Forsyth, John Haddon, Sergey Ioffe

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


Digital library applications require very general object recognition techniques. We describe an object recognition strategy that operates by grouping together image primitives in increasingly distinctive collections. Once a suciently large group has been found, we declare that an object is present. We demonstrate this method on applications such as nding unclothed people in general images and nding horses in general images. Finding clothed people is dicult, because the variation in colour and texture on the surface of clothing means that it is hard to nd regions of clothing in the image. We show that our strategy can be used to nd clothing by marking the distinctive shading patterns associated with folds in clothing, and then grouping these patterns.

Original languageEnglish (US)
Title of host publicationShape, Contour and Grouping in Computer Vision
EditorsDavid A. Forsyth, Joseph L. Mundy, Vito di Gesu, Roberto Cipolla
Number of pages17
ISBN (Print)3540667229, 9783540667223
StatePublished - 1999
Externally publishedYes
EventInternational Workshop on Shape, Contour and Grouping in Computer Vision - Palermo, Sicily, Italy
Duration: May 26 1998May 29 1998

Publication series

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


OtherInternational Workshop on Shape, Contour and Grouping in Computer Vision
CityPalermo, Sicily

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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