Free Ebook Computational Vision: Information Processing in Perception and Visual Behavior (Computational Neuroscience), by Hanspeter A. Mallot
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Computational Vision: Information Processing in Perception and Visual Behavior (Computational Neuroscience), by Hanspeter A. Mallot
Free Ebook Computational Vision: Information Processing in Perception and Visual Behavior (Computational Neuroscience), by Hanspeter A. Mallot
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This text provides an introduction to computational aspects of early vision, in particular, color, stereo, and visual navigation. It integrates approaches from psychophysics and quantitative neurobiology, as well as theories and algorithms from machine vision and photogrammetry. When presenting mathematical material, it uses detailed verbal descriptions and illustrations to clarify complex points. The text is suitable for upper-level students in neuroscience, biology, and psychology who have basic mathematical skills and are interested in studying the mathematical modeling of perception.
- Sales Rank: #1719408 in Books
- Published on: 2000-10-16
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .90" w x 7.00" l, 1.59 pounds
- Binding: Hardcover
- 320 pages
- ISBN13: 9780262133814
- Condition: Used - Like New
- Notes: 100% Satisfaction Guarantee. Tracking provided on most orders. Buy with Confidence! Millions of books sold!
About the Author
Hanspeter A. Mallot is Research Scientist at the Max Planck Institute for Biological Cybernetics at Tübingen University, Germany.
Most helpful customer reviews
1 of 1 people found the following review helpful.
One of only a handful to simplify the math without dumbing it down!
By Let's Compare Options Preptorial
First, even though the title of this book is "neuroscience," it really IS in the newer field of computational vision that includes both human and machine vision. My field is robotics, and I loved this book!
The first difference between this book and dozens of others, it that it IS a math book on computational vision, not neuron firing and spiking, and attempting to understand vision with "older biology." By this I mean that "newer" biology includes dynamical systems, differential equations, algorithms and computation, even if not overtly discussing machine vision.
The second difference is that it is one of only a few that not only cover the math, but also explain it in English so that those who don't have a year of linear algebra can also "get" it with a little effort. A few of the others include:
1. The CLASSIC by David Marr that started the whole movement of "Can this vision thing (in humans) be the brain using numerical methods to solve Fourier transforms and translate spherical geometry-- Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. This is "old" but still relevant, and you should be able to get a good deal on it used.
2. The MOST RECENT computational vision text by Davies. This is 2012, 900+ pages and NOT cheap. However, given the over 50 titles in this area, Davies is the ONLY ONE that takes the time to painstakingly explain complex engineering at a bright High School level. Not explicitly on the neuro side, but contains a LOT of computational vision topics: Computer and Machine Vision, Fourth Edition: Theory, Algorithms, Practicalities. The next closest text costs over $200 US and isn't nearly as introductory or self study student friendly. Those with a bio background will LOVE this way more than buying 5 separate image and digital signal processsing books, only to find they are way over our heads.
Beyond those two are only a few others that take the time to explain the math both with figures/ diagrams and tables as well as the English and the math: STONE: Seeing: The Computational Approach to Biological Vision; Zeki (one of the best treatments of color vision): Vision of the Brain; and Palmer: Vision Science: Photons to Phenomenology.
There are many others that cover the same material as these fine texts, but they are solid math, assume you can handle differential equations and linear algebra well, and don't give intuitive "co-explanations" for the math. This text, as well as those above, take the time to do that, making it/them ideal for introductions for students coming to math, robotics, machine vision and engineering from other areas (bio, neuro, medicine) as well as auto didacts. Highly recommended. TIP: CHECK both Amazon third parties and Abe books (amazons partner) for these titles USED for significant discounts. I DO NOT recommend these titles for e-readers like Kindle because the math formulas get slaughtered, you'll want the figures close, and you'll want to mark in the margins.
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