Perception as Bayesian Inference (Hardcover, New)

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. 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 modeling 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 written by the contributors on each other's work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	September 1996
First published:	1996
Editors:	David C. Knill • Whitman Richards
Dimensions:	254 x 178 x 29mm (L x W x T)
Format:	Hardcover
Pages:	530
Edition:	New
ISBN-13:	978-0-521-46109-2
Categories:	Books > Social sciences > Psychology > Physiological & neuro-psychology Books > Social sciences > Psychology > Cognition & cognitive psychology > Perception Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Promotions
LSN:	0-521-46109-X
Barcode:	9780521461092

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