Dr. Gary Rost Bradski is a consulting professor in the CS department at Stanford University AI Lab where he mentors robotics, machine learning and computer vision research. He is also Senior Scientist at Willow Garage http://www.willowgarage.com, a recently founded robotics research institute/incubator. He has a BS degree in EECS from U.C. Berkeley and a PhD from Boston University. He has 20 years of industrial experience applying machine learning and computer vision spanning option trading operations at First Union National Bank, to computer vision at Intel Research to machine learning in Intel Manufacturing and several startup companies in between. Gary started the Open Source Computer Vision Library (OpenCV http://sourceforge.net/projects/opencvlibrary/ ), the statistical Machine Learning Library (MLL comes with OpenCV), and the Probabilistic Network Library (PNL). OpenCV is used around the world in research, government and commercially. The vision libraries helped develop a notable part of the commercial Intel performance primitives library (IPP http://tinyurl.com/36ua5s). Gary also organized the vision team for Stanley, the Stanford robot that won the DARPA Grand Challenge autonomous race across the desert for a $2M team prize and helped found the Stanford AI Robotics project at Stanford http://www.cs.stanford.edu/group/stair/ working with Professor Andrew Ng. Gary has over 50 publications and 13 issued patents with 18 pending. He lives in Palo Alto with his wife and 3 daughters and bikes road or mountains as much as he can.
Dr. Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research includes topics in machine learning, statistical modeling, computer vision and robotics. Adrian received his Ph.D. in Theoretical Physics from Columbia university in 1998. Adrian has since 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. He has a variety of published papers and patents in physics, electrical engineering, computer science, and robotics.
发表于2024-11-25
Learning OpenCV 2024 pdf epub mobi 电子书
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、...
图书标签: OpenCV 计算机视觉 图像处理 编程 计算机科学 计算机 研究 学习
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. The second edition is updated to cover new features and changes in OpenCV 2.0, especially the C++ interface. Computer vision is everywhere - in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. 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. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book any developer or hobbyist needs to get started, 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
有opencv自带说明的就看说吧
评分有opencv自带说明的就看说吧
评分有opencv自带说明的就看说吧
评分有opencv自带说明的就看说吧
评分呵呵,出新版了呀
Learning OpenCV 2024 pdf epub mobi 电子书