Computer Vision: Principles, Algorithms, Applications, Learning

The state of the art for computer vision has undergone a revolution in the past 10 years or so. However, this 2018 edition of Davies book is surprisingly up to date. As a textbook Computer Vison provides a wide selection of topics an instructor can choose from. The coverage ranges from classical CV subjects like filters and morphology to more current methods involving deep learning. These topics are nicely divided into sections, Low Level, Intermediate Level, and Advanced. The advance topics include a good introduction to both shallow and deep machine learning, and Vison and Motion. The writing is outstandingly clear. The mathematics is kept to a minimum, which can be both a positive and a negative at the same time, depending on the course. Davies includes many useful comments on applications of machine learning, drawn from his extensive experience. As a self-study book, Computer Vision is a good starting point for understanding the theory. The level of math and the writing style make this book accessible to most beginners with college level math education. There are many cook-book style CV books available, but if one does not understand the theory you just end up pulling levers on a machine you do not understand.

The book arrived early, in great condition. Now the hard work begins...

Wow, this book is better than expected. It is a huge book!! But it is a delight as a reference book.

This book provide an excellent overview of computer vision. The style is approachable, but the content doesn't shy away from the details needed to truly gain an understanding of the techniques discussed.

The content is great, ranging from classic computer vision techniques to deep learning. Would deserve five stars but the print quality is too cheap for the price. Shame on the publisher.