Seeing, Second
Edition
The Computational Approach to Biological Vision
John P. Frisby and James V. Stone
Seeing has puzzled scientists and philosophers for
centuries and it continues to do so. This new edition of a classic text offers
an accessible but rigorous introduction to the computational approach to
understanding biological visual systems. The authors of Seeing, taking as their premise David Marr's statement that "to
understand vision by studying only neurons is like trying to understand bird
flight by studying only feathers," make use of Marr's three different
levels of analysis in the study of vision: the computational level, the
algorithmic level, and the hardware implementation level. Each chapter applies
this approach to a different topic in vision by examining the problems the
visual system encounters in interpreting retinal images and the constraints
available to solve these problems; the algorithms that can realize the
solution; and the implementation of these algorithms in neurons.
Seeing has been thoroughly
updated for this edition and expanded to more than three times its original
length. It is designed to lead the reader through the problems of vision, from
the common (but mistaken) idea that seeing consists just of making pictures in
the brain to the minutiae of how neurons collectively encode the visual
features that underpin seeing. Although it assumes no prior knowledge of the
field, some chapters present advanced material, This makes it the only textbook
suitable for both undergraduate and graduate students that takes a consistently
computational perspective, offering a firm conceptual basis for tackling the
vast literature on vision. It covers a wide range of topics, including
aftereffects, the retina, receptive fields, object recognition, brain maps,
Bayesian perception, motion, color, and stereopsis.
MatLab code is available on the book's Web site, which
includes a simple demonstration of image convolution.