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Learning OpenCV: Computer Vision with the OpenCV Library Paperback – 4 Oct 2008

4.2 out of 5 stars 6 customer reviews

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Product details

  • Paperback: 580 pages
  • Publisher: O'Reilly Media; 1 edition (4 Oct. 2008)
  • Language: English
  • ISBN-10: 0596516134
  • ISBN-13: 978-0596516130
  • Product Dimensions: 17.8 x 3 x 23.3 cm
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Bestsellers Rank: 396,483 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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.


Customer Reviews

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Top Customer Reviews

Format: Paperback 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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Format: Paperback 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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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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