Understanding Vision: theory, models, and data
by Li Zhaoping


Understanding Vision: theory, models, and data

-- a book (by Oxford University Press) published May 2014

Teaching and learning support --- materials are being added to this page as they become available


Chapter 1: Approach and Scope

Figures in a pptx file


Chapter 2: A Very Brief Introduction of What is Known about Vision Experimentally

Figures in a pptx file


Chapter 3: The Efficient Coding Principle

Figures in a pptx file

A one-hour video of an introductory lecture

A playlist of more than 40 short video lectures (about 10 minutes each)

Slides from a lecture on this topic in ACCN 2014 summer school


Chapter 4: V1 and Information Coding

Figures in a pptx file


Chapter 5: The V1 Hypothesis - Creating a Bottom up Saliency map for Preattentive Selection and Segmentation.

You can read it in the sample chapters of the book

Figures in a pptx file

A video of an introductory lecture

This is the video of a presentation (its slides) at the plenary symposium "Visual perception meets computational neuroscience" at ECVP 2013 could be used as a short introduction to this chapter


Chapter 6: Visual Recognition as Decoding.

Figures in a pptx file

Two video lectures of introductory tutorial

Slides from a lecture on color discrimination (cf. section 6.3.4 of the book) in Kongsberg Vision Meeting Oct. 2014


Chapter 7: Epilogue .

A blog article Are we too "smart" to understand how we see?



This review paper below may be seen as a very abbreviated version of some selected sections in chapters 3-5 of the book :.

L. Zhaoping (2006) Theoretical Understanding of early visual processes by data compression and data selection in Network: Computation in neural systems 17(4):301-334 (2006).