I 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 c

I 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