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- W2126399818 abstract "The misjudgement of tilt in images lies at the heart of entertaining visual illusions and rigorous perceptual psychophysics. A wealth of findings has attracted many mechanistic models, but few clear computational principles. We adopt a Bayesian approach to perceptual tilt estimation, showing how a smoothness prior offers a powerful way of addressing much confusing data. In particular, we faithfully model recent results showing that confidence in estimation can be systematically affected by the same aspects of images that affect bias. Confidence is central to Bayesian modeling approaches, and is applicable in many other perceptual domains." @default.
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- W2126399818 date "2005-12-05" @default.
- W2126399818 modified "2023-09-23" @default.
- W2126399818 title "A Bayesian Framework for Tilt Perception and Confidence" @default.
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