Gary Bradski博士是斯坦福大学人工智能实验室的顾问教授,也是Willow Garage公司机器人学研究协会的资深科学家。
Adrian Kaehler博士,Applied Minds公司的资深科学家,从事机器学习、统计建模、计算机视觉和机器人学方面的研究。
Description
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. With this book, any developer or hobbyist can get up and running with the framework quickly, whether it's to build simple or sophisticated vision applications.
Full Description
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 on building computer vision applications of your own.
这本《学习OpenCV》是O’Reilly出品于2008年,旋即由刘瑞祯和于仕琪在国内翻译出版。 相比国人介绍函数使用方法的书,《学习OpenCV》的着眼点则更多的回到图形图像,配合专业基础的脉络来介绍OpenCV。 作为基础教程,那类似于Hello World是一定要的,而一本书的好坏,从Hello...
评分"Because we are nice people and like our code to be readable and easy to understand, we adopt the convention of adding a leading g_ to any global variable. " Funny as it goes, the book is a practical & followable handbook for first opencv learners. Beside...
评分作者从与Sebastian Thrun研发Stanley以及与Andrew Ng研究Stair开始。 这本书的内容有点过时,不过对于了解opencv的起源和基本架构还是很有帮助的。 IPP库的应用,说明起初的opencv更加偏向底层 在所有资料里,这本书对于图像处理基本算法的分析解释应该是最简明最清楚的 p273 ...
评分这本《学习OpenCV》是O’Reilly出品于2008年,旋即由刘瑞祯和于仕琪在国内翻译出版。 相比国人介绍函数使用方法的书,《学习OpenCV》的着眼点则更多的回到图形图像,配合专业基础的脉络来介绍OpenCV。 作为基础教程,那类似于Hello World是一定要的,而一本书的好坏,从Hello...
评分作者从与Sebastian Thrun研发Stanley以及与Andrew Ng研究Stair开始。 这本书的内容有点过时,不过对于了解opencv的起源和基本架构还是很有帮助的。 IPP库的应用,说明起初的opencv更加偏向底层 在所有资料里,这本书对于图像处理基本算法的分析解释应该是最简明最清楚的 p273 ...
读得酣畅淋漓 可惜Computer vision 的知识太欠缺了
评分CH1-5
评分很不错的入门材料
评分近期唯一一本正经OpenCV书,有点薄。
评分很不错的入门材料
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