On the inverse problem of binocular 3D motion perception

Lages, M. and Heron, S. (2010) On the inverse problem of binocular 3D motion perception. PLoS Computational Biology, 6(11), e1000999. (doi: 10.1371/journal.pcbi.1000999)

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It is shown that existing processing schemes of 3D motion perception such as interocular velocity difference, changing disparity over time, as well as joint encoding of motion and disparity, do not offer a general solution to the inverse optics problem of local binocular 3D motion. Instead we suggest that local velocity constraints in combination with binocular disparity and other depth cues provide a more flexible framework for the solution of the inverse problem. In the context of the aperture problem we derive predictions from two plausible default strategies: (1) the vector normal prefers slow motion in 3D whereas (2) the cyclopean average is based on slow motion in 2D. Predicting perceived motion directions for ambiguous line motion provides an opportunity to distinguish between these strategies of 3D motion processing. Our theoretical results suggest that velocity constraints and disparity from feature tracking are needed to solve the inverse problem of 3D motion perception. It seems plausible that motion and disparity input is processed in parallel and integrated late in the visual processing hierarchy.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Lages, Dr Martin and Heron, Miss Suzanne
Authors: Lages, M., and Heron, S.
College/School:College of Science and Engineering > School of Psychology
Journal Name:PLoS Computational Biology
Publisher:Public Library of Science
ISSN (Online):1553-7358
Published Online:18 November 2010
Copyright Holders:Copyright © 2010 The Authors
First Published:First published in PLoS Computational Biology 6(11):e100099
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
449881Social interaction - a cognitive-neurosciences approachSimon GarrodEconomic & Social Research Council (ESRC)ES/E020933/1Cognitive Neuroimaging & Neuroengineering Technologies