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.
OpenCV(Open source Computer Vision library,开放计算机视觉库)由Intel发起,采用C/C++编写,追求性能优化,跨平台,帮助新生从一个高的起点开始视觉研究,避免闭门造车。 在CentOS-2.6.32中安装OpenCV-2.2.0步骤: (1)安装相关依赖工程(本人只装了yasm、ffmpeg、...
评分OpenCV(Open source Computer Vision library,开放计算机视觉库)由Intel发起,采用C/C++编写,追求性能优化,跨平台,帮助新生从一个高的起点开始视觉研究,避免闭门造车。 在CentOS-2.6.32中安装OpenCV-2.2.0步骤: (1)安装相关依赖工程(本人只装了yasm、ffmpeg、...
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,...
评分本书充满了丰富的应用OpenCV编程的例子,对于OpenCV库函数的介绍也大多是通过例子的方式完成的。可以说,这样厚厚的一本书,对于OpenCV 1.0中的几乎所有的库函数均有所涉及。我认为,与传统的手册型Manual具有不同的风格,该书更像是一个OpenCV的工作人员在叙说整个OpenCV的方...
评分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...
把code里的bug排掉,注上编译的方法避免分散读者注意力,这本书就更好了。
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。
评分读的中文版的,讲解的还是很清楚的,也不拖泥带水!
评分近期唯一一本正经OpenCV书,有点薄。
评分读的中文版的,讲解的还是很清楚的,也不拖泥带水!
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