图像处理与计算机视觉：基础，经典以及最近发展（5）计算机视觉

Last update: 2012-6-7

这一章是计算机视觉部分，主要侧重在底层特征提取，视频分析，跟踪，目标检测和识别方面等方面。对于自己不太熟悉的领域比如摄像机标定和立体视觉，仅仅列出上google上引用次数比较多的文献。有一些刚刚出版的文章，个人非常喜欢，也列出来了。

本章的下载地址：

http://iask.sina.com.cn/u/2252291285/ish?folderid=868772

1. Active Appearance Models

活动表观模型和活动轮廓模型基本思想来源Snake，现在在人脸三维建模方面得到了很成功的应用，这里列出了三篇最初最经典的文章。对这个领域有兴趣的可以从这三篇文章开始入手。

[1998 ECCV] ActiveAppearance Models

[2001 PAMI] ActiveAppearance Models

 

2. Active Shape Models

[1995 CVIU]Active ShapeModels-Their Training and Application

 

3. Background modeling andsubtraction

背景建模一直是视频分析尤其是目标检测中的一项关键技术。虽然最近一直有一些新技术的产生，demo效果也很好，比如基于dynamical texture的方法。但最经典的还是Stauffer等在1999年和2000年提出的GMM方法，他们最大的贡献在于不用EM去做高斯拟合，而是采用了一种迭代的算法，这样就不需要保存很多帧的数据，节省了buffer。Zivkovic在2004年的ICPR和PAMI上提出了动态确定高斯数目的方法，把混合高斯模型做到了极致。这种方法效果也很好，而且易于实现。在OpenCV中有现成的函数可以调用。在背景建模大家族里，无参数方法（2000 ECCV）和Vibe方法也值得关注。

[1997 PAMI] PfinderReal-Time Tracking of the Human Body

[1999 CVPR] Adaptivebackground mixture models for real-time tracking

[1999 ICCV] WallflowerPrinciples and Practice of Background Maintenance

[2000 ECCV] Non-parametricModel for Background Subtraction

[2000 PAMI] LearningPatterns of Activity Using Real-Time Tracking

[2002 PIEEE] Backgroundand foreground modeling using nonparametric kernel density estimation forvisual surveillance

[2004 ICPR] Improvedadaptive Gaussian mixture model for background subtraction

[2004 PAMI] Recursiveunsupervised learning of finite mixture models

[2006 PRL] Efficientadaptive density estimation per image pixel for the task of backgroundsubtraction

[2011 TIP] ViBe AUniversal Background Subtraction Algorithm for Video Sequences

 

4.  Bag of Words

词袋，在这方面暂时没有什么研究。列出三篇引用率很高的文章，以后逐步解剖之。

[2003 ICCV] Video Google AText Retrieval Approach to Object Matching in Videos

[2004 ECCV] VisualCategorization with Bags of Keypoints

[2006 CVPR] Beyond bags offeatures Spatial pyramid matching for recognizing natural scene categories

 

5.  BRIEF

BRIEF是BinaryRobust Independent Elementary Features的简称，是近年来比较受关注的特征描述的方法。ORB也是基于BRIEF的。

[2010 ECCV] BRIEF BinaryRobust Independent Elementary Features

[2011 ICCV] ORB anefficient alternative to SIFT or SURF

[2012 PAMI] BRIEFComputing a Local Binary Descriptor Very Fast

 

6. Camera Calibration and StereoVision

非常不熟悉的领域。仅仅列出了十来篇重要的文献，供以后学习。

[1979 Marr] AComputational Theory of Human Stereo Vision

[1985] Computationalvision and regularization theory

[1987 IEEE] A versatilecamera calibration technique for high-accuracy 3D machine vision metrologyusing off-the-shelf TV cameras and lenses

[1987] ProbabilisticSolution of Ill-Posed Problems in Computational Vision

[1988 PIEEE] Ill-PosedProblems in Early Vision

[1989 IJCV] KalmanFilter-based Algorithms for Estimating Depth from Image Sequences

[1990 IJCV] RelativeOrientation

[1990 IJCV] Usingvanishing points for camera calibration

[1992 ECCV] Cameraself-calibration Theory and experiments

[1992 IJCV] A theory ofself-calibration of a moving camera

[1992 PAMI] Cameracalibration with distortion models and accuracy evaluation