Understanding Vision: Theory, Models, and Data by Li Zhaoping (PDF)

Description

While the field of vision science has grown significantly in the past three decades, there have been few comprehensive books that showed readers how to adopt a computional approach to understanding visual perception, along with the underlying mechanisms in the brain.Understanding Vision explains the computational principles and models of biological visual processing, and in particular, of primate vision. The book is written in such a way that vision scientists, unfamiliar with mathematical details, should be able to conceptually follow the theoretical principles and their relationship with physiological, anatomical, and psychological observations, without going through the more mathematical pages. For those with a physical science background, especiallythose from machine vision, this book serves as an analytical introduction to biological vision. It can be used as a textbook or a reference book in a vision course, or a computational neuroscience course for graduate students or advanced undergraduate students. It is also suitable for self-learning bymotivated readers.in addition, for those with a focused interest in just one of the topics in the book, it is feasible to read just the chapter on this topic without having read or fully comprehended the other chapters. In particular, Chapter 2 presents a brief overview of experimental observations on biological vision; Chapter 3 is on encoding of visual inputs, Chapter 5 is on visual attentional selection driven by sensory inputs, and Chapter 6 is on visual perception or decoding.Including many examples that clearly illustrate the application of computational principles to experimental observations, Understanding Vision is valuable for students and researchers in computational neuroscience, vision science, machine and computer vision, as well as physicists interested in visual processes.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐The worst book I have ever read. Disorder logic, poor English, unclear explanation.

⭐This is an excellent book in which the author shows how elegant computational theories explain and predict complex and puzzling experimental findings in vision. The author has been a leading expert in the field and the expositions are both authoritative and lucid. There are many illuminative examples throughout the book that are presented not only mathematically but also intuitively. As such, I believe the book provides an extremely valuable resource for a broad range of readers. For example, it can serve as either a reference book for active researchers or a textbook for graduate and advanced undergraduate students. The book covers some of the most important topics in vision including encoding (how the brain cells respond to the world), decoding (how those responses produce our subjective perception of the world), and attention (how the brain filters and selects information in the world). When I learned from the book how seemingly arbitrary and unrelated physiological and behavioral phenomena (some of which I studied years ago) all fit together in beautiful mathematical or computational frameworks, I truly feel the excitement of being enlightened. There is no doubt that people in many different fields, including systems neuroscience, computational neuroscience, and machine vision, will benefit greatly from reading this book.

⭐”This book is much better than David Marr’s ‘Vision’!”

⭐Very well written book!Some colleague did comment that it has too many equations but I think it is worth putting them there. Definitely recommend it.

⭐Il testo offre una panoramica approfondita dei vari aspetti che riguardano il sistema di visione umano,modelli matematici, sistemi biologicamente ispirati e descrizione approfondita dei vari meccanismidella percezione visiva. Altamente consigliato

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