Bayesian models of binocular 3-D motion perception.

Martin Lages

doi:10.1167/6.4.14

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Bayesian models of binocular 3-D motion perception.

Martin Lages

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Abstract

Psychophysical studies on three-dimensional (3-D) motion perception have shown that perceived trajectory angles of a small target traveling in depth are systematically biased. Here, predictions from Bayesian models, which extend existing models of motion-first and stereo-first processing, are investigated. These statistical models are based on stochastic representations of monocular velocity and binocular disparity input in a binocular viewing geometry. The assumption of noise in these inputs together with a plausible prior for 3-D motion leads to testable predictions of perceived trajectory angle and velocity. Results from two experiments are reported, suggesting that disparity rather than motion processing introduces perceptual bias.

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Bayes Theorem Depth Perception Humans Models, Psychological Motion Perception Photic Stimulation Psychophysics Time Factors Vision Disparity Vision, Binocular Vision, Monocular Journal Article Research Support, Non-U.S. Gov't

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Martin Lages. 2006-07-20. Bayesian models of binocular 3-D motion perception.. https://doi.org/10.1167/6.4.14

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