Reading list for beginners in Computer Vision area (updated Aug 22, 2014)

Here’s my recommendation of reading list for beginners in Computer Vision area.

General Tutorials:

Best tutorial ever for beginners in CV area. Prof. Prince provides free e-print file and all the algorithms with elegant matlab implementations on his website. You can even find a lot of slides and faq on it. Enjoy!

Computer Vision: A Modern Approach, 2nd Edition by David A. Forsyth is also excellent but seems relatively advanced and not that strongly related to the trending machine learning methods.

Computer Vision: Algorithms and Applications by Richard Szeliski is a good manual for reference but seems too fragmental thus not appropriate for beginners. You can get some whole pictures from this book, then quickly jump to CVMLI to get more machine learning based ideas.

Classical textbook from which you could learn more about the image pre-processing for computer vision.

Application Tutorials:

You could find corresponding Matlab implementations based on the above theory-oriented version.

You might also be interested in Mastering OpenCV with Practical Computer Vision Projects, by Daniel Baggio, if you want to build some fancy projects based on Android, iOS and Microsoft Kinect.

Math Review:

The Open Course from Prof. Gilbert Strang is also a good supplementary material for self-study.

As it claims, a friendly introduction for Electrical and Computer Engineers.

MOOC on Coursera:

Beginner friendly.

Great course, actually every beginner should take it.

Courses and Notes:

Great course for basic ideas of Deep Learning.

Useful practical for Deep Learning based on Matlab.

Extra Machine Learning Tutorial:

More suitable for beginners than PRML from Prof. Bishop. It also provides all the Matlab implementations from which you will benifit a lot.

Interesting machine learning tutorial based on Python. You can implement some tiny real systems quickly and be happy.