Where is the light? Bayesian perceptual priors for lighting direction
Identifieur interne : 004060 ( Main/Merge ); précédent : 004059; suivant : 004061Where is the light? Bayesian perceptual priors for lighting direction
Auteurs : J. V. Stone [Royaume-Uni] ; I. S. Kerrigan [Royaume-Uni] ; J. Porrill [Royaume-Uni]Source :
- Proceedings of the Royal Society B: Biological Sciences [ 0962-8452 ] ; 2009.
Abstract
Perception of shaded three-dimensional figures is inherently ambiguous, but this ambiguity can be resolved if the brain assumes that figures are lit from a specific direction. Under the Bayesian framework, the visual system assigns a weighting to each possible direction, and these weightings define a prior probability distribution for light-source direction. Here, we describe a non-parametric maximum-likelihood estimation method for finding the prior distribution for lighting direction. Our results suggest that each observer has a distinct prior distribution, with non-zero values in all directions, but with a peak which indicates observers are biased to expect light to come from above left. The implications of these results for estimating general perceptual priors are discussed.
Url:
DOI: 10.1098/rspb.2008.1635
PubMed: 19324801
PubMed Central: 2674484
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<front><div type="abstract" xml:lang="en"><p>Perception of shaded three-dimensional figures is inherently ambiguous, but this ambiguity can be resolved if the brain assumes that figures are lit from a specific direction. Under the Bayesian framework, the visual system assigns a weighting to each possible direction, and these weightings define a prior probability distribution for light-source direction. Here, we describe a non-parametric maximum-likelihood estimation method for finding the prior distribution for lighting direction. Our results suggest that each observer has a distinct prior distribution, with non-zero values in all directions, but with a peak which indicates observers are biased to expect light to come from above left. The implications of these results for estimating general perceptual priors are discussed.</p>
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