I'm trying to write a new computer vision textbook. I'm going to post updated versions here as I do so. The plan is to first teach probability and machine learning and then present each chapter as a different model with associated learning and inference algorithms.
Now completed first draft of the applications, problems, and literature review up to the end of Chapter 11 (Markov Random Fields). Fixed numerous errors. Thanks particularly to James Tompkin and Yun Fu for helping find these.
New update yesterday - now completed first draft of Applications, References, Algorithm and Problems up to chapter 9 and working on chapter 10. Various small errors found in earlier chapters and corrected.