Perception as Bayesian Inference

Name: Perception as Bayesian Inference
Price: 54.0 USD
Availability: InStock
ISBN: 9780521064996

ISBN-10: 0521064996

ISBN-13: 9780521064996

Edition: 2008

Authors: David C. Knill, Whitman Richards

List price: $76.99

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Description:

Bayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. This book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modelling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries…

Book details

List price: $76.99
Copyright year: 2008
Publisher: Cambridge University Press
Publication date: 6/12/2008
Binding: Paperback
Pages: 532
Size: 6.97" wide x 9.96" long x 1.02" tall
Weight: 2.002

Whitman Richards is currently Professor Emeritus in the Department of Brain and Cognitive Sciences at MIT, and is affiliated with MIT's Computer Science and Artificial Intelligence Lab (CSAIL). He has been a member of MIT's faculty for fifty years.




Introduction




Pattern theory: a unifying perspective




Modal structure and reliable inference




Priors, preferences and categorical percepts




Bayesian decision theory and psychophysics




Observer theory, Bayes theory, and psychophysics




Implications of a Bayesian formulation




Shape from texture: ideal observers and human psychophysics




A computational theory for binocular stereopsis




The generic viewpoint assumption in a Bayesian framework




Experiencing and perceiving visual surfaces




The perception of shading and reflectance




Banishing the Homunculus