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よく一緒に購入されている商品
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内容説明
"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.
著者について
Dr. Gary Rost Bradski is VP of Technology at Rexee Inc. a new startup applying machine learning to rich media on the web. He is also a consulting professor in the CS department at Stanford University, AI Lab where he mentors robotics, machine learning and computer vision research. He has a BS degree in EECS from U.C. Berkeley and a PhD from Boston University.Dr. Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research includes topics in machine learning, statistical modeling, and computer vision. Adrian received his Ph.D. in Theoretical Physics from Columbia university in 1998. Adrian 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.
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この商品を見た後に買っているのは？
カスタマーレビュー
Amazon.com で最も参考になったカスタマーレビュー (beta)
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29件のカスタマーレビュー
46 人中、46人の方が、｢このレビューが参考になった｣と投票しています。
A great guide to OpenCV with plenty of context
2008/10/30
形式:ペーパーバック|Amazonが確認した購入
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.
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.
42 人中、40人の方が、｢このレビューが参考になった｣と投票しています。
Lacking the C++ API
2010/11/19
形式:ペーパーバック|Amazonが確認した購入
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.
6 人中、6人の方が、｢このレビューが参考になった｣と投票しています。
An absolute must have!!!
2008/10/21
形式:ペーパーバック
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.
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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