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Martin Lages; Bayesian models of binocular 3-D motion perception. Journal of Vision 2006;6(4):14. doi: 10.1167/6.4.14.
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© 2016 Association for Research in Vision and Ophthalmology.
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.
Note. * p < .05.
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