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.
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...
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...
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...
OpenCV作者写的书,是最好的OpenCV教材
评分OpenCV作者写的书,是最好的OpenCV教材
评分球推荐图像解析入门书
评分把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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