Stereo integration, mean field theory and psychophysics

A. L. Yuille, D. Geiger, H. Bülthoff

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


We describe a theoretical formulation for stereo in terms of the Markov Random Field and Bayesian approach to vision. This formulation enables us to integrate the depth information from different types of matching primitives, or from different vision modules. We treat the correspondence problem and surface interpolation as different aspects of the same problem and solve them simultaneously, unlike most previous theories. We use techniques from statistical physics to compute properties of our theory and show how it relates to previous work. These techniques also suggest novel algorithms for stereo which are argued to be preferable to standard algorithms on theoretical and experimental grounds. It can be shown (Yuille, Geiger and Bülthoff 1989) that the theory is consistent with some psychophysical experiments which investigate the relative importance of different matching primitives.

Original languageEnglish (US)
Title of host publicationComputer Vision – ECCV 1990 - 1st European Conference on Computer Vision, Proceedings
EditorsOlivier Faugeras
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783540525226
StatePublished - 1990
Event1st European Conference on Computer Vision, ECCV 1990 - Antibes, France
Duration: Apr 23 1990Apr 27 1990

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume427 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other1st European Conference on Computer Vision, ECCV 1990

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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