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Understanding Vision: theory, models, and data
by Li Zhaoping
Understanding Vision: theory, models, and data
-- a book (by Oxford University Press) published May 2014
click here for the publisher's UK webpage (and here for its US webpage) for this book, and also available from various online sites and shops worldwide.
It is also available at oxfordscholarshiponline at
http://dx.doi.org/10.1093/acprof:oso/9780199564668.001.0001
Teaching and learning support --- materials are being added to this page as they become available
Chapter 2: A Very Brief Introduction of What is Known about Vision Experimentally
Chapter 3: The Efficient Coding Principle
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
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
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.
Two video lectures of introductory tutorial
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).
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