Dr. Gary Rost Bradski is a consulting professor in the CS department at Stanford University AI Lab where he mentors robotics, machine learning and computer vision research. He is also Senior Scientist at Willow Garage http://www.willowgarage.com, a recently founded robotics research institute/incubator. He has a BS degree in EECS from U.C. Berkeley and a PhD from Boston University. He has 20 years of industrial experience applying machine learning and computer vision spanning option trading operations at First Union National Bank, to computer vision at Intel Research to machine learning in Intel Manufacturing and several startup companies in between. Gary started the Open Source Computer Vision Library (OpenCV http://sourceforge.net/projects/opencvlibrary/ ), the statistical Machine Learning Library (MLL comes with OpenCV), and the Probabilistic Network Library (PNL). OpenCV is used around the world in research, government and commercially. The vision libraries helped develop a notable part of the commercial Intel performance primitives library (IPP http://tinyurl.com/36ua5s). Gary also organized the vision team for Stanley, the Stanford robot that won the DARPA Grand Challenge autonomous race across the desert for a $2M team prize and helped found the Stanford AI Robotics project at Stanford http://www.cs.stanford.edu/group/stair/ working with Professor Andrew Ng. Gary has over 50 publications and 13 issued patents with 18 pending. He lives in Palo Alto with his wife and 3 daughters and bikes road or mountains as much as he can.
Dr. Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research includes topics in machine learning, statistical modeling, computer vision and robotics. Adrian received his Ph.D. in Theoretical Physics from Columbia university in 1998. Adrian has since held positions at Intel Corporation and the Stanford University AI Lab, and was a member of the winning Stanley race team in the DARPA Grand Challenge. He has a variety of published papers and patents in physics, electrical engineering, computer science, and robotics.
The book is very well written, with very nice examples and explanations.
This book is excellent at exposing the reader to the various methods available in OpenCV and showing via code examples how to use each one.
This book is much more than a programming guide to the open source computer vision programming library, OpenCV.
IMHO, OpenCV is the de-facto computer vision library for folks interested in robotic applications with vision. Read morePublished 4 months ago by William Macaluso
This book is an excellent book. There is a 2nd edition coming out in 2014 so please get that, instead of this one. That being said, its a very very good book.Published 8 months ago by davydany
Despite all the evolution that OpenCV has gone through these last five years, and all the available on-line documentation and newer books that have been published, this is still... Read morePublished 10 months ago by David M. Stanwick
I put off buying this for a long time because I thought I could get everything I was looking for online. Read morePublished 12 months ago by Mreff555
This is a great book with everything you need to learn the basics of OpenCV.
And besides all the theory, the author gives the reader a lot of examples and practical methods so... Read more
This book was invaluable when I was developing some integration with security cameras and also a game testing and automation framework. Read morePublished 13 months ago by Jason Martin
I like this book as a supplement to understand how opencv works and how you should construct your program. Read morePublished 14 months ago by Ayse Elvan Gunduz
OpenCV is a wonderful imaging and matrix API. The presentation is very strong, with some good photos and examples. Read morePublished 15 months ago by James D. Cook
The programming examples in the book no longer work. Many of the OpenCV procedures now require additional parameters to be specified. The book needs to be updated.Published 17 months ago by R. Feretich