Media praise for Learning OpenCV
"Learning OpenCV provides a unified and clear presentation of the both the underlying theory and the practical use of contemporary computer vision techniques that are an essential component of building vision systems that interact with the real-world. "
"Gary Bradksi has done the computer vision community a great service by organizing and championing the OpenCV library. This library is useful for practicioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."
"Learning OpenCV will likely occupy a prominent spot on the bookshelf of almost anyone working in computer vision...As readers, we are fortunate to have this chance to learn about OpenCV directly from Gary Bradski, who was the driving force and prime developer behind OpenCV. With his coauthor, Adrian Kaehler, they provide a clear and well-thought-out overview of the entire OpenCV code base, with many simple introductory examples that make it easy to slowly gain expertise with this large library of software. "
"Gary Bradski, the primary developer of OpenCV, and co-author Adrian Kaehler, have done an excellent job in writing this book. The chapters are written in a highly user-friendly fashion, with clear explanations and hands-on examples. The book can be used as both a reference book to the OpenCV library as well as a tutorial or text for many fundamental concepts in computer vision. This is a must-have book on any computer vision bookshelf. "
"This highly accessible book should be of great value to anyone interested in building and understanding computer vision applications. It fills an important gap between many more theoretically-oriented textbooks in the field of computer vision, by providing a highly accessible hands-on guide on how to build actual computer vision software. If you are like me, you will find it a pleasure to read, and full of insights. This is a highly practical book."
"This book's main job is to provide an introduction to OpenCV. It does that very well. It does something more: it reviews clearly and concisely many of the main concepts in machine vision. The book may be used to support an introductory machine vision course, picking up where the lectures left off and holding the students' hand in bringing what they learned in class to life."
-- , Director of the National Science Foundation Engineering Research Center in Neuromorphic Systems Engineering
"The book provides a clearly written introduction and tutorial that makes computer vision applications accessible to a range of new audiences."
"Computer vision combines theory and experimentation, and the latter requires a daunting amount of sophisticated algorithms and complex data structures even to get started. The OpenCV software library is a precious tool for new students and seasoned researchers alike, as it provides perhaps the only open-source, comprehensive collection of blocks for building state-of-the-art computer vision code. Learning OpenCV provides a conceptual framework for this well-maintained and optimized collection of software, and makes its components accessible through clear background explanations, a thorough yet simple description of the function interfaces, and well chosen, attractive examples. Much more than a user manual, this book would form an excellent basis for a hands-on, introductory course in computer vision. "
-- , Duke University
"This book by two leading roboticists is much more than a programming guide for how to call functions in a programming library. You will enjoy the trip through practical application of Computer Vision and the overview of Machine Learning."
-- , Amazon.com
"...definitely a very useful and highly recommended introduction and reference. "
-- , Computer Science House