- Paperback: 555 pages
- Publisher: O'Reilly Media; 1st edition (October 4, 2008)
- Language: English
- ISBN-10: 0596516134
- ISBN-13: 978-0596516130
- Product Dimensions: 7 x 1.2 x 9.2 inches
- Shipping Weight: 1.7 pounds (View shipping rates and policies)
- Average Customer Review: 4.0 out of 5 stars See all reviews (49 customer reviews)
Amazon Best Sellers Rank:
#362,724 in Books (See Top 100 in Books)
- #11 in Books > Computers & Technology > Hardware & DIY > Microprocessors & System Design > DSPs
- #58 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Computer Vision & Pattern Recognition
- #84 in Books > Computers & Technology > Programming > Languages & Tools > C & C++ > Tutorials
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Learning OpenCV: Computer Vision with the OpenCV Library 1st Edition
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About the Author
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.
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Top Customer Reviews
This book would be most useful to someone who already has a fundamental understanding of computer vision and image processing and wants to see how OpenCV will make their programming tasks easier. It does this by coding up well known algorithms into reliable pieces of code that you can use to accomplish more complex tasks. Do not come to this book if you are seeking to learn computer vision. You will only be confused as the author does not offer enough detail to teach you the mathematical foundations. However, I don't think that was his intention at all. Instead it is part user manual, part basic computer vision tutorial and overview, and part idea book. Each chapter is supplemented with excellent and interesting programming exercises that test your knowledge of what has been presented in a practical setting.
For a good basic understanding of computer vision try Computer Vision. To understand the algorithmic underpinnings of 3D computer vision try Introductory Techniques for 3-D Computer Vision.Read more ›
If you are just a CV hobbyist, and just want to create some computer vision app with a webcam and don't care about the math, there's tons of resource online on how to use the library effectively.
I give the book four stars instead of five because I wish it would give more programming examples that it does. And sometimes the language is a little hard to understand, I'd usually have to read it several times to grasp the concepts in the book.
The book also includes many references and pointers to other material (such as technical papers), allowing the reader to learn more about any topic covered.
This is a great reference book, that won't just sit on your self.
The writing style is a bit too casual sometimes. I have been a tiny bit annoyed by the authors' breezy treatment of some important details that I'm struggling with. Nevertheless, there just isn't a better alternative, or anything even close. I guess I should be grateful that the alternative isn't the case: excessive, impenetrable formality!
Again, this is still the best OpenCV reference available right now.
About a year ago Amazon listed the second edition of this book for pre-order. Months went by, and they eventually canceled it. What's up with that?
Most Recent Customer Reviews
Great resource. Used as reference for my CS course. Still relevant even though it's based on an old release of OpenCv (explanations of most algorithms still apply, and function... Read morePublished 7 months ago by Dyl
Not useful at all. All the sample codes are coded in C. Are you kidding me? Nobody is using C anymore, at least C++Published 7 months ago by Amazon Customer
This explains things a bit better than the online tutorials I've found but is written for the pre-3. Read morePublished 9 months ago by M. Schippling
Book is too dated. I'd wait to get the newer C++ version to be release. A lot of the old code in this book does not really applies anymore.Published 11 months ago by Amazon Customer
a little bit outdated but the new edition is coming on october, if you really want to understand how OpenCV works you need to read the theory of this book!! Read morePublished 18 months ago by Talek