Perception as Bayesian Inference

Herausgeber: Knill, David C.; Richards, Whitman

• Gebundenes Buch

Produktbeschreibung

In recent years, 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. The Bayesian approach provides new and powerful metaphors for conceptualizing visual perception, suggests novel questions to ask about perceptual processing, and provides the means to formalize theories of perception that make testable predictions about human perceptual performance. This book provides an introduction to and critical analysis of the Bayesian paradigm. Chapters by leading researchers in computational theory and experimental visual science introduce new theoretical frameworks for building perceptual theories, discuss the implications of the Bayesian paradigm for psychophysical studies of human perception, and describe specific applications of the approach. The editors have created a critical dialogue of ideas through the authors' commentaries on each others' chapters, conveying to the reader a unique appreciation for the issues and ideas raised in the book.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 530
• Erscheinungstermin: 17. Mai 2011
• Englisch
• Abmessung: 260mm x 183mm x 33mm
• Gewicht: 1183g
• ISBN-13: 9780521461092
• ISBN-10: 052146109X
• Artikelnr.: 21251161

Inhaltsangabe

1. Introduction D. C. Knill, D. Kersten and A. Yuille; 2. Pattern theory: a
unifying perspective D. Mumford; 3. Modal structure and reliable inference
A. Jepson, W. Richards and D. C. Knill; 4. Priors, preferences and
categorical percepts W. Richards, A. Jepson and J. Feldman; 5. Bayesian
decision theory and psychophysics A. L. Yuille and H. H. Bulthoff; 6.
Observer theory, Bayes theory, and psychophysics B. M. Bennett, D. D.
Hoffman, C. Prakash and S. N. Richman; 7. Implications of a Bayesian
formulation D. C. Knill, D. Kersten and P. Mamassian; 8. Shape from
texture: ideal observers and human psychophysics A. Blake, H. H. Bulthoff
and D. Sheinberg; 9. A computational theory for binocular stereopsis P. N.
Belhumeur; 10. The generic viewpoint assumption in a Bayesian framework W.
T. Freeman; 11. Experiencing and perceiving visual surfaces K. Nakayama and
S. Shimojo; 12. The perception of shading and reflectance E. H. Adelson and
A. P. Pentland; 13. Banishing the Homunculus H. Barlow.