Does anybody know of some good, comprehensive book (free or paid) with guide to all the algorithms available in OpenCV and how to use them, approachable for a "common programmer"? (i.e. for somebody with approximately zero knowledge of image recognition terminology). I'd be very interested in reading one; when looking purely at the API docs, I'm totally lost.
The OpenCV Python API is actually pretty good. I've been compiling and using the latest stuff off of master for the past couple years and when I took Computer Vision Fall 2013 at GMU.
However, I don't think that much of it is generally useful without a basic understanding of CV. The documentation is pretty good[0], but it will be hard to apply them without understanding the tradeoffs.
The CV courses I've taken focused a lot on lecture slides and handouts rather than a comprehensive textbook (although I've heard good things about Programming Computer Vision with Python[1] as an introductory text).
I think you might be surprised with how easy it is to use the basic functions of OpenCV. Just get started, poke around with it, and you'll start getting more familiar with it and able to understand the more advanced stuff.
Also, the documentation has a lot of tutorials available. It's pretty good.
Not exactly what you asked, but... SimpleCV is a derivative project of OpenCV that's easy to dive into it and worth considering. O'Reilly published the short book "Practical Computer Vision" on it. Easy to go from that to OpenCV after some practice.
Seconded. I have a specific application in mind. My current approach is an IPython notebook (with OpenCV 2) and trial and error to find a combination of algorithms that work, but I'm not convinced I'm using the correct algorithms at all.
