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Most of my attempts at getting into CV fail because my knowledge of Maths is incredibly rusty. I did Maths up to university level, but haven't used it since. A
by weavie 10y ago
Most of my attempts at getting into CV fail because my knowledge of Maths is incredibly rusty. I did Maths up to university level, but haven't used it since.
Are there any good courses / books or other resources that would specifically help at getting up to speed with the maths knowledge required to understand a book like this?
- randcraw 10y agoI can't recommend Szeliski's or Prince's book as a good first text in CV. Szeliski's is unnecessarily math heavy and lacks worked examples or explanations of concepts. It's esentially a reference book. Prince's is (reputedly) excellent at approaching CV from a ML perspective, but it doesn't really cover the main concepts in CV, so it's a poor source for the fundamentals. Davies' book "Computer and Machine Vision" is the least math intensive CV text I've found. Its emphasis is more on MV (industrial vision) than CV, but it covers the basics of CV pretty well. Klette's "Concise Computer Vision" recent (2014) has good coverage of CV, but it is concise (oft short explanations), and DO NOT buy the Kindle version. It fails to render a custom font used by the author, so some of the most important characters within are invisible. Trucco and Verri's "Intro Techniques for 3D Vision" (1998) is clear and short though a bit dated, but it covers the basics well. Likewise Shapiro & Stockman (2001) is a well written survey but also dated. I like both. Avoid the Forsyth & Ponce book unless you're a masochist. Very unclear exposition. I like the GaTech CV video course (the free videos are part of their online MS in CS, OMSCS). Essa and Bobick's presentations are clear and lively, the coverage broad. They don't use a text. Also, the videos from Shah's course CV at Central Florida are available on Youtube. He offers good clear coverage of the topic, though without enthusiasm. https://www.omscs.gatech.edu/cs-4495-computer-vision https://www.omscs.gatech.edu/cs-4495-computer-vision
- joshvm 10y agoI wouldn't recommend Szeliski for that - the book is basically a literature review (and is now a little out of date given how fast CV moves). It's great if you need a background survey on how things are done, but not for learning from. The level of maths required varies a lot. Linear algebra is used heavily everywhere, you see a lot of optimisation (e.g. Levenberg Marquadt) and in some places graph theory. However if you're just using tools like OpenCV then you can get by with a fairly poor understanding of the maths (say 2nd year undergrad of an engineering degree). Part of the challenge is reading past the maths. If you read a paper from Pattern Analysis there's a lot of, frankly, obtuse notation. So you see images described as discrete mapping blah blah. A lot of it is fairly straightforward set theory. It's necessary for proving things, but when it comes to actually implementing this stuff it's nowhere near as complicated as it looks.
- weavie 10y agoYes I think the notation is quite a stumbling block. Eg, As soon as I see an integral sign I am lost. I have no idea how to transform that into an algorithm.