机器视觉技术基础知识（你想了解的都在这里）

这两周，一直奔波于各种杂物，能留给看书，写东西的时间却越发少了总觉得很可惜好在今天在Git Hub 上翻到了一些好东西计算机视觉领域，你需要了解的都在这里了或许以后要给自己定个规矩，每周都要留下两三天就看资料，写东西才好腹无点墨，以后是怕要是更找不到妹子了话说根据新的广告法，若是大家转发给我介绍对象，是不是也得标注广告了？，我来为大家讲解一下关于机器视觉技术基础知识?跟着小编一起来看一看吧!

机器视觉技术基础知识

这两周，一直奔波于各种杂物，能留给看书，写东西的时间却越发少了。总觉得很可惜。好在今天在Git Hub 上翻到了一些好东西。计算机视觉领域，你需要了解的都在这里了。或许以后要给自己定个规矩，每周都要留下两三天就看资料，写东西才好。腹无点墨，以后是怕要是更找不到妹子了。话说根据新的广告法，若是大家转发给我介绍对象，是不是也得标注广告了？

OH No！！！！！无论新广告法怎样，但今天有个大安利，我是安利定了。今天在Git Hub 上翻到了一个项目，整理了计算机视觉领域的相关资料。计算机视觉领域，你需要了解的几乎都在这里了。如过你也想对这个项目做出贡献，你可以 email 项目的发起者 Jia-Bin Huang（jbhuang1@illinois.edu） 由于微信不能外链，很多贴出来的书目都有数字版的文档，大家可以在后台回复 十全大补丸 获取原文链接。

计算机视觉十全大补丸

发起人Jia-Bin Huang

研究方向： physically grounded visual synthesis and analysis.

书

计算机视觉：

Computer Vision: Models, Learning, and

Inference- Simon J. D. Prince 2012

Computer Vision: Theory and Application - Rick Szeliski 2010

Computer Vision: A Modern Approach (2nd edition) - David Forsyth and Jean Ponce 2011

Multiple View Geometry in Computer Vision - Richard Hartley and Andrew Zisserman 2004

Computer Vision - Linda G. Shapiro 2001

Vision Science: Photons to Phenomenology - Stephen E. Palmer 1999

Visual Object Recognition synthesis lecture - Kristen Grauman and Bastian Leibe 2011

Computer Vision for Visual Effects - Richard J. Radke, 2012

High dynamic range imaging: acquisition, display, and image-based lighting - Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics - Justin Solomon 2015

OpenCV Programming：

Learning OpenCV: Computer Vision with the OpenCV Library - Gary Bradski and Adrian Kaehler

Practical Python and OpenCV - Adrian Rosebrock

OpenCV Essentials - Oscar Deniz Suarez, Mª del Milagro

Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia

机器学习：

Pattern Recognition and Machine Learning - Christopher M. Bishop 2007

Neural Networks for Pattern Recognition - Christopher M. Bishop 1995

Probabilistic Graphical Models: Principles and Techniques - Daphne Koller and Nir Friedman 2009

Pattern Classification - Peter E. Hart, David G. Stork, and Richard O. Duda 2000

Machine Learning - Tom M. Mitchell 1997

Gaussian processes for machine learning - Carl Edward Rasmussen and Christopher K. I. Williams 2005

Learning From Data- Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin 2012

Neural Networks and Deep Learning - Michael Nielsen 2014

Bayesian Reasoning and Machine Learning - David Barber, Cambridge University Press, 2012

基础：Linear Algebra and Its Applications - Gilbert Strang 1995

课程

计算机视觉：

EENG 512 / CSCI 512 - Computer Vision - William Hoff (Colorado School of Mines)

Visual Object and Activity Recognition - Alexei A. Efros and Trevor Darrell (UC Berkeley)

Computer Vision - Steve Seitz (University of Washington)

Visual Recognition - Kristen Grauman (UT Austin)

Language and Vision - Tamara Berg (UNC Chapel Hill)

Convolutional Neural Networks for Visual Recognition - Fei-Fei Li and Andrej Karpathy (Stanford University)

Computer Vision - Rob Fergus (NYU)

Computer Vision - Derek Hoiem (UIUC)

Computer Vision: Foundations and Applications - Kalanit Grill-Spector and Fei-Fei Li (Stanford University)

High-Level Vision: Behaviors, Neurons and Computational Models - Fei-Fei Li (Stanford University)

Advances in Computer Vision - Antonio Torralba and Bill Freeman (MIT)

Computer Vision - Bastian Leibe (RWTH Aachen University)

Computer Vision 2 - Bastian Leibe (RWTH Aachen University)

Computational Photography：

Image Manipulation and Computational Photography - Alexei A. Efros (UC Berkeley)

Computational Photography - Alexei A. Efros (CMU)

Computational Photography - Derek Hoiem (UIUC)

Computational Photography - James Hays (Brown University)

Digital & Computational Photography - Fredo Durand (MIT)

Computational Camera and Photography - Ramesh Raskar (MIT Media Lab)

Computational Photography - Irfan Essa (Georgia Tech)

Courses in Graphics - Stanford UniversityComputational Photography - Rob Fergus (NYU)

Introduction to Visual Computing - Kyros Kutulakos (University of Toronto)

Computational Photography - Kyros Kutulakos (University of Toronto)

Computer Vision for Visual Effects - Rich Radke (Rensselaer Polytechnic Institute)

Introduction to Image Processing - Rich Radke (Rensselaer Polytechnic Institute)

机器学习：

Machine Learning - Andrew Ng (Stanford University)

Learning from Data - Yaser S. Abu-Mostafa (Caltech)

Statistical Learning - Trevor Hastie and Rob Tibshirani (Stanford University)

Statistical Learning Theory and Applications - Tomaso Poggio, Lorenzo Rosasco, Carlo Ciliberto, Charlie Frogner, Georgios Evangelopoulos, Ben Deen (MIT)

Statistical Learning - Genevera Allen (Rice University)

Practical Machine Learning - Michael Jordan (UC Berkeley)

Course on Information Theory, Pattern Recognition, and Neural Networks - David MacKay (University of Cambridge)

Methods for Applied Statistics: Unsupervised Learning - Lester Mackey (Stanford)

Machine Learning - Andrew Zisserman (University of Oxford)

优化：

Convex Optimization I - Stephen Boyd (Stanford University)

Convex Optimization II - Stephen Boyd (Stanford University)

Convex Optimization - Stephen Boyd (Stanford University)

Optimization at MIT - (MIT)

Convex Optimization - Ryan Tibshirani (CMU)

未完待续

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