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...
评分说实话 国内外目前比较好的 值得深入一读的书籍不多,此书值得深入读下去,不仅涉及到我所研究的图像图形,还有视频类的处理。opencv里很多代码都是基于C的,比较好懂,而且图像视频从感官上来说是一个容易吸引人的领域,从学术角度讲,有理论有理论,有实践有实践,是标准的工...
评分和ARM LINUX 结合起来就比较纠结了。 第一次接触图像处理,一个开源跨平台的函数库。 做完这个项目估计就不会再接触了,书还是挺经典的。 美式的教学和书籍编写风格,显得不那么枯燥。 函数形式很简单,结合具体事例的时候会比较纠结, 特别是在ARM虚拟机下的摄像头图像采集,...
评分Opencv数字图像处理交流群:168464432,欢迎大家加入群交流学习,共同进步,在群里大家可以探讨有关数字图像处理,机器视觉领域的前沿和技术问题,一起努力提高。验证信息:豆瓣网 Opencv数字图像处理交流群:168464432,欢迎大家加入群交流学习,共同进步,在群里大家可...
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...
比较基础,不过因为我是用的python包,所以很多函数的形式都变了。
评分CH1-5
评分opencv经典入门书
评分这本书其实还是工具书,初学的话,把图像矩阵的基础知识那几章读了就行。后面用的时候,大部分时候都是直接Google的
评分书确实是本经典好书,只可惜讲的是1.0版C语言实现的接口;GitHub上看了下已经几乎全部换成C++实现,而且据说2.X版本接口变化很大;所以暂时只粗略翻了下,以后想深入了解理论的话也许会再回过头来细看;目前除了官方文档,可能带实例的入门类书籍更适合我。
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