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Learning OpenCV: Computer Vision with the OpenCV Library


By Gary Bradski, Adrian Kaehler
 
Image of: Learning OpenCV: Computer Vision with the OpenCV Library
Pricing Details:

List Price:$49.99
You save:$5.86 (11.7%)
Your Price:$44.13
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Book Details:

Format:Paperback, 555 pages.
Publisher:O'Reilly Media, Inc. 2008-10-03
ISBN:0596516134

Average Customer Rating:

5.0 5 out of 5 stars (5 reviews)

Editorial Reviews:

Learning OpenCV puts you right in the middle of the rapidly expanding field of computer vision. Written by the creators of OpenCV, the widely used free open-source 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 the data. Computer vision is everywhere -- in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It helps robot cars drive by themselves, stitches Google maps and Google Earth together, checks the pixels on your laptop's LCD screen, and makes sure the stitches in your shirt are OK. OpenCV provides an easy-to-use computer vision infrastructure along with a comprehensive library containing more than 500 functions that can run vision code in real time. With Learning OpenCV, any developer or hobbyist can get up and running with the framework quickly, whether it's to build simple or sophisticated vision applications. The book includes: A thorough introduction to OpenCV Getting input from cameras Transforming images Shape matching Pattern recognition, including face detection Segmenting images Tracking and motion in 2 and 3 dimensions Machine learning algorithms

Hands-on exercises at the end of each chapter help you absorb the concepts, and an appendix explains how to set up an OpenCV project in Visual Studio. OpenCV is written in performance optimized C/C++ code, runs on Windows, Linux, and Mac OS X, and is free for commercial and research use under a BSD license. Getting machines to see is a challenging but entertaining goal. If you're intrigued by the possibilities, Learning OpenCV gets you started onbuilding computer vision applications of your own.


Customer Reviews:

5 out of 5 stars Awesome - wish I had this years ago

After years of plodding through the discussion group and limited HTML based docs and puzzling out how to make OpenCV work finally a tell-all book that makes this worlds class tool accessible to all!

5 out of 5 stars This book is GREAT !!!

Very well written, excellent introduction, beautiful clear figures and illustrations, excellent balance between text, equations, figures, and source code, just the right level of intuitive v.s. technical v.s. mathematical explanation, great explanations of complex algorithmic concepts, with just the right touch of humor here and there to brighten up the dry technical talk, and apparently, a very clear and useful and well designed computer vision software package in that OpenCV, which the author also wrote, with the wonderful advantage that the software is totally free and open source!

5 out of 5 stars Great way to get started

Covers the details quickly so that you can get started coding and covers the right way to access data so that you can maintain the speed necessary for computer vision applications. I've found this book to be really helpful in getting started with OpenCV as well as digging into some of the finer details of some of it's machine learning capabilities.

5 out of 5 stars A great guide to OpenCV with plenty of context

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. However, before you read either of these you must read Digital Image Processing (3rd Edition), since image processing concepts are fundamental to understanding computer vision tasks. In fact, the two disciplines overlap in many spots. The sad truth of the matter is that no one book will teach you what you need to know to be an effective image scientist. However, this book on OpenCV is essential reading on applying the theory via programming in an effective manner. Highly recommended.

5 out of 5 stars An absolute must have!!!

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.


Customers who bought this book were also interested in:


Multiple View Geometry in Computer Vision


Feature Extraction & Image Processing, Second Edition


Pattern Recognition and Machine Learning (Information Science and Statistics)


Programming Collective Intelligence: Building Smart Web 2.0 Applications


Digital Image Processing (3rd Edition)

 

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Last updated: Sat Nov 22 8:34:42 CST 2008
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