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Bayesian combination of ambiguous shape cues

Record type: Article

We investigate how different depth cues are combined when one cue is ambiguous. Convex and concave surfaces produce similar texture projections at large viewing distances. Our study considered unambiguous disparity information and its combination with ambiguous texture information. Specifically, we asked whether disparity and texture were processed separately, before linear combination of shape estimates, or jointly, such that disparity disambiguated the texture information.Vertical ridges of various depths were presented stereoscopically. Their texture was consistent (in terms of maximum likelihood) with both a convex and a concave ridge. Disparity was consistent with either a convex or concave ridge. In a separate experiment the stimuli were defined solely by texture (monocular viewing). Under monocular viewing observers consistently reported the convex interpretation of the texture cue. However, in stereoscopic stimuli, texture information modulated shape from disparity in a way inconsistent with simple linear combination. When disparity indicated a concave surface, a texture pattern perceived as highly convex when viewed monocularly caused the stimulus to appear more concave than a “flat” texture pattern. Our data confirm that different cues can disambiguate each other. Data from both experiments are well modeled by a Bayesian approach incorporating a prior for convexity.

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Citation

Adams, Wendy J. and Mamassian, Pascal (2004) Bayesian combination of ambiguous shape cues Journal of Vision, 4, (10), pp. 921-929. (doi:10.1167/4.10.7).

More information

Published date: 1 November 2004
Keywords: cue-combination, depth, texture, stereo, disparity, bayes, bayesian

Identifiers

Local EPrints ID: 39948
URI: http://eprints.soton.ac.uk/id/eprint/39948
ISSN: 1534-7362
PURE UUID: c4b72cd0-3e83-4d2c-af5f-56f1d7213601
ORCID for Wendy J. Adams: ORCID iD orcid.org/0000-0002-5832-1056

Catalogue record

Date deposited: 05 Jul 2006
Last modified: 17 Jul 2017 15:35

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Contributors

Author: Wendy J. Adams ORCID iD
Author: Pascal Mamassian

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