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Learning OpenCV: Computer Vision with the OpenCV Library Paperback – October 1, 2008

ISBN-13: 978-0596516130 ISBN-10: 0596516134 Edition: 1st

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Product Details

  • Paperback: 555 pages
  • Publisher: O'Reilly Media; 1st edition (October 1, 2008)
  • Language: English
  • ISBN-10: 0596516134
  • ISBN-13: 978-0596516130
  • Product Dimensions: 9.2 x 7 x 1.2 inches
  • Shipping Weight: 1.7 pounds (View shipping rates and policies)
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (37 customer reviews)
  • Amazon Best Sellers Rank: #85,453 in Books (See Top 100 in Books)

Editorial Reviews

Book Description

Software That Sees

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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Customer Reviews

The book is very well written, with very nice examples and explanations.
JN
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.
calvinnme
This book is much more than a programming guide to the open source computer vision programming library, OpenCV.
Ira Laefsky

Most Helpful Customer Reviews

51 of 51 people found the following review helpful By calvinnme HALL OF FAMETOP 500 REVIEWERVINE VOICE on October 30, 2008
Format: Paperback Verified Purchase
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. The author also gives you the website where you can look at the actual source code of each method shown. This is helpful since, for example, if you want to know exactly how the code is going about calculating the Fundamental Matrix, it is difficult to determine this by reading the book alone.

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.
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58 of 62 people found the following review helpful By Peter Harrington on November 18, 2010
Format: Paperback Verified Purchase
I really love OpenCV. I bought this book and read about 50% of it before starting a project. Initially I found some code on the internet that looked like OpenCV code but was lacking pointers and casts. I learned that this clean code is actually C++ code with heavy use of templates in OpenCV 2.0. Sadly the book is based on OpenCV 1.0, so very little of the code in the book is useable.
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8 of 8 people found the following review helpful By Jean-Yves Bouguet on October 20, 2008
Format: Paperback
At last a practical, pragmatic, accessible book on computer vision (and more!) providing step by step guidance on fundamental computational vision topics, with algorithmic explanation (just what is needed!), and concrete example code snippets. This book is now opening the door to the fabulous world of computational vision to anyone. It gives immediate access to a vast collection of image processing, and machine learning functions, all open source!
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.
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5 of 5 people found the following review helpful By William A. Barrett on April 11, 2010
Format: Paperback Verified Purchase
As a computer instructor and researcher in biometrics and pattern recognition, I welcome this treatise on OpenCV.
Don't even consider opening the pages unless you are familiar with C, its use of structs, pointers, callback functions and the like. You may also be put off by the various mathematical discussions of various advanced computer vision algorithms that have been developed over the last two decades.
OpenCV is an open-source collaborative work. It's partially supported by the Intel corporation, through their quest for advanced algorithms that might be included in its computer chips. Many low-level tools needed for video and image processing are now provided in advanced Intel microprocessors.
The theme of OpenCV is audacious, yet achievable -- that of providing high-quality, high-performance software tools for the many computer vision algorithms that have been published over the years. That has largely been achieved through the clever use of low-level pointer-based tools, accompanied by complete C source code for everything down to the raw processor instructions.
Other good news is that the system provides an easy portal to advanced Intel hardware support, boosting performance to the highest possible level. One can also port OpenCV-based code to Linux, other Unix and Mac platforms -- it is not restricted to Windows.
I've had some trouble with Windows XP, but the image and camera grabbing functions work well under Windows Vista. I've also been able to exploit the OpenCV tools under Windows MFC to support Windows-based applications.
This O'Reilly book provides the background support that you will need to download the OpenCV system from the internet, configure your development environment and start exploring the magic that its tools can provide.
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4 of 4 people found the following review helpful By howlowck on December 17, 2010
Format: Paperback
This is a great book on the library. Although it's rather old and lacks the new C++ API (which, to me, is very similar to the MATLAB image processing toolkit), it provides a rather detailed explanation on the inner workings of the library as well as the math and research papers that backs it up.

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.
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