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转Tutorial papers for MRF, CRF and DRF

2012-02-25T00:45:00Z

In this article I compile a list of good papers and tutorials related to MRFs, CRFs and DRFs. Hopefully you will find it useful.

Recently I have been interested in conditional random fields (CRFs) for image modeling/labeling. I had really difficult time finding good materials to read. In this post, I would like to dedicate to people who are having a difficult time understanding CRFs, particularly, for image classification. My goal is to save your time by pointing you out to some good and useful materials, so that you don’t have to waste a lot of time like I did in past few weeks.

You might come up with some questions like what are the differences between CRF vs Bayesian networks (BNs) or between CRF vs MRF? What are the advantages of CRFs which are discriminative models over generative models like MRF and BN? What are the relationships between CRFs and other fundamental statistics models e.g. logistic regression and log-linear model? and most importantly…I’m a newbie..where should I get started?

Here are the list of materials:

Log-linear Models and Conditional Random Fields by Charles Elkanhttp://videolectures.net/cikm08_elkan_llmacrf/ . I think this should be the first material you might want to learn from. The instructor did a really good job giving the overview of fundamental topics on statistics, e.g. maximum likelihood, logistic regression, log-linear model, then connect the idea to CRF at the end. However, in this lecture, there is not much connection between CRFs and other graphical models.
Discriminative Random Fields (IJCV paper) by Sanjiv Kumar and Martial Hebert. For me, this is the best paper talking about CRFs for image classification/labeling. The paper discusses about MRF, BN in brief, then points out the main problems using those models, and shows how CRF can solve the existing problems.
Models for Learning Spatial Interactions in Natural Images for Context-Based Classification (PhD thesis) by Sanjiv Kumar. If you like the paper [2] above and would like to see more detail of how to derive some learning formula, then you might want to see the PhD thesis of this paper which provides a lot mode details and images for better understanding.
An Introduction to Conditional Random Fields for Relational Learning by Sutton, C., McCallum, A. (tutorial paper). This is a good and pretty long tutorial paper. What I like in this paper is that the paper motivates readers by some good examples especially in natural language processing which is a good application to show the power of CRFs. Another good thing is that this paper shows some connections between CRFs and some other graphical models.

At some point, you might feel that CRFs are closely related to MRFs. For those who are not familiar to MRFs, there are some good books and papers I would lkike to recommend:

Markov random field modeling in image analysis by Stan Z. Li — This might be the best book on MRFs so far as it explains almost everything about MRFs in considerable details ranging from Gibbs random fields, MRFs, CRFs, DRFs, energy functions, smoothness constrains, learning algorithms, inference algorithms, etc. I really recommend this book if you have TIME to read it. However, this book seems to focus more on theoretical than real example aspect.
Image processing: dealing with texture by Maria Petrou & Pedro García Sevilla — I like this book because there are a lot of good examples on how MRFs, energy functions, etc look like in practice. This would be a good book to read parallel to the book from Stan Z. Li.
Image analysis, random fields, and dynamic Monte Carlo methods: a mathematical introduction by Gerhard Winkler
Markov Random Field Models: A Bayesian Approach to Computer Vision Problems (technical report) by Gerda Kamberova. — This is a free, good , and concise report on MRFs or computer vision.

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转 QT无法定位程序输入点*于动态链接库 QtCore4.dll

2011-07-20T01:50:00Z

问题:

双击release下的exe文件报错，无法定位程序输入点与动态链接库QtCore4.dll上，而debug下没问题将release下的exe文件拷到qt的bin目录下，再双击就没问题了.

我的回复:

我也出现了这个问题.
原因很有可能是你环境变量中的系统变量PATH设置问题.
我开始安装QT没有出现这个问题,用了一段时间就出现罗.
觉得是 QtCore4.dll 链接错误,意思是说 release下的可执行程序链接的QtCore4.dll不是QT安装目录下的/bin中的QtCore4.dll.
后来一查找,发现最近安装的CTEX软件中也有QtCore4.dll,找到原因了.
所以,把qt下的库路径添加到我CTEX库路径之前,就解决问题啦.

这是一种典型的动态库连接错误问题.动态链接库QtCore.dll有多个版本,发生冲突.

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难道一直是4 4 2 3的命？

2011-06-10T07:45:00Z

vis 2010是 4 4 2 3；

eurovis 2011 是 4 4 2 3；

vis 2011 4 4 2 3；

难道这是我的宿命？

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bibtex to bibitem

2011-05-04T01:01:00Z

\documentclass{article}

\begin{document}

\nocite{*}

\bibliography{xxx}

\bibliographystyle{plain}

\end{document}

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再次被rejected

2010-06-08T04:48:00Z

虽然预料到，但还是有点不甘心

4 4 2 3被拒，primary reviewer推荐到tvcg,但还是被paper chair rejected

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qt ogl添加keyevent

2010-03-25T08:57:00Z

qt对ogl程序添加keyevent,一定要加上以下两句:setFocusPolicy(Qt::StrongFocus);installEventFilter(parent)

牛年最后一天的rejection

2010-02-17T03:45:00Z

完全能上的paper,被自己的大意糟蹋掉了所有的reviewer对idea都很喜欢，可惜自己竟然没有解释为什么它能workfigure1竟然用了不能扣题的数据，可谓是最大的失误今年的vis里再也不能犯同样的错误了。不过圆满了，三大VIS都有被拒的文章

cg 如何给结构体数组赋值

2009-07-25T12:11:00Z

以前没用过，今天折腾了很久才学会。 CGparameter Param = cgGetNamedParameter(m_raycastFrag, "aaa"); //读structure of array参数 cgSetArraySize(Param,num);//设置数组大小for (int i=0;i

cg fp40的问题

2009-07-25T12:03:00Z

程序的shader要用到三重循环，用cgc编译后，shader代码没问题。然而cgCreateProgramFromFile时，却怎么得过去不，而且让内存从几兆一下上升到几百兆。开始没有debug,还以为电脑中了病毒。debug发现该问题后，想到可能是fp40不支持三重循环的shader,然后换用gp4fp解决该问题。

cg又一个数据绑定错误

2009-07-25T12:00:00Z

TextureManager::getGaussTF(gaussParam); 该函数通过引用方式读取gaussParam参数，然后绑定到cg的某一参数。然而，如果该函数放在cgGLBindProgram(xxx)后执行，无法得到争取的gaussParam。开始以为是引用问题，后改为传值，一样的错误。最后发现，必须把该函数放到cgglBIndProgram前执行。-----------------...