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Learning OpenCV: Computer Vision with the OpenCV Library [Paperback]

Gary Bradski , Adrian Kaehler
4.4 out of 5 stars  See all reviews (5 customer reviews)
RRP: £38.50
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Learning OpenCV: Computer Vision in C++ with the OpenCV Library Learning OpenCV: Computer Vision in C++ with the OpenCV Library
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Book Description

1 Oct 2008 0596516134 978-0596516130 1

"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."
-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology

Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.

Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.

Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:

  • A thorough introduction to OpenCV
  • Getting input from cameras
  • Transforming images
  • Segmenting images and shape matching
  • Pattern recognition, including face detection
  • Tracking and motion in 2 and 3 dimensions
  • 3D reconstruction from stereo vision
  • Machine learning algorithms

Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.


Frequently Bought Together

Learning OpenCV: Computer Vision with the OpenCV Library + OpenCV 2 Computer Vision Application Programming Cookbook + Algorithms for Image Processing and Computer Vision
Price For All Three: £91.73

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Product details

  • Paperback: 580 pages
  • Publisher: O'Reilly Media; 1 edition (1 Oct 2008)
  • Language: English
  • ISBN-10: 0596516134
  • ISBN-13: 978-0596516130
  • Product Dimensions: 17.9 x 3 x 23.2 cm
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Bestsellers Rank: 115,471 in Books (See Top 100 in Books)
  • See Complete Table of Contents

More About the Author

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Product Description

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

4.4 out of 5 stars
4.4 out of 5 stars
Most Helpful Customer Reviews
2 of 2 people found the following review helpful
4.0 out of 5 stars So close to easy 10 Nov 2008
Format:Paperback|Amazon Verified Purchase
The book encourages early attempts at jumping in; however, this is a mistake as the early examples simply are not complete and they won't work.
However, persevere with the book and the OpenCV free library, and you will be richly rewarded.
You simply must make extensive use of the index to dig up the information necessary for completion of the first examples, and perseverence will leave you with a basic test structure into which you can plug the many image processing functions with minimal changes.
This is fun.
Frankly I haven't got the video working yet, and frankly I've been more interested in the static processing since my job needs this more.
I've got the libraries working on both Linux and XP, with splendid, visually impressive, results.
When I get more time I'll be working through to the advanced examples.
Meanwhile, I recommend recent versions of KDevelop-c/c++ if you are working on Linux; the Library dependencies are even easier than windows.
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1 of 1 people found the following review helpful
5.0 out of 5 stars Excellent! 18 Feb 2010
Format:Paperback|Amazon Verified Purchase
This is a great book, providing an excellent introduction in OpenCV. The balance between theory and practical examples is very well chosen. The book could serve equally newcomers and experienced readers. There are a few things that you might need looking up in some cases, but the important thing is, that with this book you can start using OpenCV efficiently easily and fast.
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3 of 4 people found the following review helpful
3.0 out of 5 stars Good book, bad examples 20 May 2010
By A. Nagy
Format:Paperback
I've purchased this book to learn OPenCV and gain understand theory behind computer vision techniques. The book is excellent introducing to the library and the concepts behind it. It is very well organized and written very professionally. You sure need to go out there sometimes and find more material on specific algorithms or concepts but the book does a good job giving you a startup.

What is bad about this book...
One bad star of the clarity of examples. However examples work, they lack proper code documentation and written in a bad C style. High level comment exist (sometimes) but you cannot follow up the code of 400 lines example unless you go for online documentation or spend hours trying to figure out what's hapenning. Methods parameters in the examples , command line argumernts, variables...etc are all not documented.

Another bad star for OpenCV. Good work by intel, but as far as I remember, C++ has been there for some decades now. It makes no sense to me to have all huge library entities and algorithms written in C. To construct an object (which are typically structures), they follow naming conventions like constructors do not exist. One more thing, some enums and defs completely lack documentation, and again you have to find examples for them which are sometimes hard to find.
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