二零一三年计算机视觉代码合集

一、特征提取Feature Extraction：

SIFT [1] [Demo program][SIFT Library] [VLFeat]
PCA-SIFT [2] [Project]
Affine-SIFT [3] [Project]
SURF [4] [OpenSURF] [Matlab Wrapper]
Affine Covariant Features [5] [Oxford project]
MSER [6] [Oxford project] [VLFeat]
Geometric Blur [7] [Code]
Local Self-Similarity Descriptor [8] [Oxford implementation]
Global and Efficient Self-Similarity [9] [Code]
Histogram of Oriented Graidents [10] [INRIA Object Localization Toolkit] [OLT toolkit for Windows]
GIST [11] [Project]
Shape Context [12] [Project]
Color Descriptor [13] [Project]
Pyramids of Histograms of Oriented Gradients [Code]
Space-Time Interest Points (STIP) [14][Project] [Code]
Boundary Preserving Dense Local Regions [15][Project]
Weighted Histogram[Code]
Histogram-based Interest Points Detectors[Paper][Code]
An OpenCV - C++ implementation of Local Self Similarity Descriptors [Project]
Fast Sparse Representation with Prototypes[Project]
Corner Detection [Project]
AGAST Corner Detector: faster than FAST and even FAST-ER[Project]
Real-time Facial Feature Detection using Conditional Regression Forests[Project]
Global and Efficient Self-Similarity for Object Classification and Detection[code]
WαSH: Weighted α-Shapes for Local Feature Detection[Project]
HOG[Project]
Online Selection of Discriminative Tracking Features[Project]

二、图像分割Image Segmentation：

Normalized Cut [1] [Matlab code]
Gerg Mori’ Superpixel code [2] [Matlab code]
Efficient Graph-based Image Segmentation [3] [C++ code] [Matlab wrapper]
Mean-Shift Image Segmentation [4] [EDISON C++ code] [Matlab wrapper]
OWT-UCM Hierarchical Segmentation [5] [Resources]
Turbepixels [6] [Matlab code 32bit] [Matlab code 64bit] [Updated code]
Quick-Shift [7] [VLFeat]
SLIC Superpixels [8] [Project]
Segmentation by Minimum Code Length [9] [Project]
Biased Normalized Cut [10] [Project]
Segmentation Tree [11-12] [Project]
Entropy Rate Superpixel Segmentation [13] [Code]
Fast Approximate Energy Minimization via Graph Cuts[Paper][Code]
Efﬁcient Planar Graph Cuts with Applications in Computer Vision[Paper][Code]
Isoperimetric Graph Partitioning for Image Segmentation[Paper][Code]
Random Walks for Image Segmentation[Paper][Code]
Blossom V: A new implementation of a minimum cost perfect matching algorithm[Code]
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision[Paper][Code]
Geodesic Star Convexity for Interactive Image Segmentation[Project]
Contour Detection and Image Segmentation Resources[Project][Code]
Biased Normalized Cuts[Project]
Max-flow/min-cut[Project]
Chan-Vese Segmentation using Level Set[Project]
A Toolbox of Level Set Methods[Project]
Re-initialization Free Level Set Evolution via Reaction Diffusion[Project]
Improved C-V active contour model[Paper][Code]
A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction[Paper][Code]
Level Set Method Research by Chunming Li[Project]
ClassCut for Unsupervised Class Segmentation[code]
SEEDS: Superpixels Extracted via Energy-Driven Sampling [Project][other]

三、目标检测Object Detection：

A simple object detector with boosting [Project]
INRIA Object Detection and Localization Toolkit [1] [Project]
Discriminatively Trained Deformable Part Models [2] [Project]
Cascade Object Detection with Deformable Part Models [3] [Project]
Poselet [4] [Project]
Implicit Shape Model [5] [Project]
Viola and Jones’s Face Detection [6] [Project]
Bayesian Modelling of Dyanmic Scenes for Object Detection[Paper][Code]
Hand detection using multiple proposals[Project]
Color Constancy, Intrinsic Images, and Shape Estimation[Paper][Code]
Discriminatively trained deformable part models[Project]
Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD [Project]
Image Processing On Line[Project]
Robust Optical Flow Estimation[Project]
Where's Waldo: Matching People in Images of Crowds[Project]
Scalable Multi-class Object Detection[Project]
Class-Specific Hough Forests for Object Detection[Project]
Deformed Lattice Detection In Real-World Images[Project]
Discriminatively trained deformable part models[Project]

四、显著性检测Saliency Detection：

Itti, Koch, and Niebur’ saliency detection [1] [Matlab code]
Frequency-tuned salient region detection [2] [Project]
Saliency detection using maximum symmetric surround [3] [Project]
Attention via Information Maximization [4] [Matlab code]
Context-aware saliency detection [5] [Matlab code]
Graph-based visual saliency [6] [Matlab code]
Saliency detection: A spectral residual approach. [7] [Matlab code]
Segmenting salient objects from images and videos. [8] [Matlab code]
Saliency Using Natural statistics. [9] [Matlab code]
Discriminant Saliency for Visual Recognition from Cluttered Scenes. [10] [Code]
Learning to Predict Where Humans Look [11] [Project]
Global Contrast based Salient Region Detection [12] [Project]
Bayesian Saliency via Low and Mid Level Cues[Project]
Top-Down Visual Saliency via Joint CRF and Dictionary Learning[Paper][Code]
Saliency Detection: A Spectral Residual Approach[Code]

五、图像分类、聚类Image Classification, Clustering

Pyramid Match [1] [Project]
Spatial Pyramid Matching [2] [Code]
Locality-constrained Linear Coding [3] [Project] [Matlab code]
Sparse Coding [4] [Project] [Matlab code]
Texture Classification [5] [Project]
Multiple Kernels for Image Classification [6] [Project]
Feature Combination [7] [Project]
SuperParsing [Code]
Large Scale Correlation Clustering Optimization[Matlab code]
Detecting and Sketching the Common[Project]
Self-Tuning Spectral Clustering[Project][Code]
User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior[Paper][Code]
Filters for Texture Classification[Project]
Multiple Kernel Learning for Image Classification[Project]
SLIC Superpixels[Project]

六、抠图Image Matting

A Closed Form Solution to Natural Image Matting [Code]
Spectral Matting [Project]
Learning-based Matting [Code]

七、目标跟踪Object Tracking：

A Forest of Sensors - Tracking Adaptive Background Mixture Models [Project]
Object Tracking via Partial Least Squares Analysis[Paper][Code]
Robust Object Tracking with Online Multiple Instance Learning[Paper][Code]
Online Visual Tracking with Histograms and Articulating Blocks[Project]
Incremental Learning for Robust Visual Tracking[Project]
Real-time Compressive Tracking[Project]
Robust Object Tracking via Sparsity-based Collaborative Model[Project]
Visual Tracking via Adaptive Structural Local Sparse Appearance Model[Project]
Online Discriminative Object Tracking with Local Sparse Representation[Paper][Code]
Superpixel Tracking[Project]
Learning Hierarchical Image Representation with Sparsity, Saliency and Locality[Paper][Code]
Online Multiple Support Instance Tracking [Paper][Code]
Visual Tracking with Online Multiple Instance Learning[Project]
Object detection and recognition[Project]
Compressive Sensing Resources[Project]
Robust Real-Time Visual Tracking using Pixel-Wise Posteriors[Project]
Tracking-Learning-Detection[Project][OpenTLD/C++ Code]
the HandVu：vision-based hand gesture interface[Project]
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities[Project]

八、Kinect：

Kinect toolbox[Project]
OpenNI[Project]
zouxy09 CSDN Blog[Resource]
FingerTracker 手指跟踪[code]

九、3D相关：

3D Reconstruction of a Moving Object[Paper] [Code]
Shape From Shading Using Linear Approximation[Code]
Combining Shape from Shading and Stereo Depth Maps[Project][Code]
Shape from Shading: A Survey[Paper][Code]
A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)[Project][Code]
Multi-camera Scene Reconstruction via Graph Cuts[Paper][Code]
A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination[Paper][Code]
Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture[Project]
Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers[Code]
Learning 3-D Scene Structure from a Single Still Image[Project]

十、机器学习算法：

Matlab class for computing Approximate Nearest Nieghbor (ANN) [Matlab class providing interface toANN library]
Random Sampling[code]
Probabilistic Latent Semantic Analysis (pLSA)[Code]
FASTANN and FASTCLUSTER for approximate k-means (AKM)[Project]
Fast Intersection / Additive Kernel SVMs[Project]
SVM[Code]
Ensemble learning[Project]
Deep Learning[Net]
Deep Learning Methods for Vision[Project]
Neural Network for Recognition of Handwritten Digits[Project]
Training a deep autoencoder or a classifier on MNIST digits[Project]
THE MNIST DATABASE of handwritten digits[Project]
Ersatz：deep neural networks in the cloud[Project]
Deep Learning [Project]
sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++[Project]
Weka 3: Data Mining Software in Java[Project]
Invited talk "A Tutorial on Deep Learning" by Dr. Kai Yu (余凯)[Video]
CNN - Convolutional neural network class[Matlab Tool]
Yann LeCun's Publications[Wedsite]
LeNet-5, convolutional neural networks[Project]
Training a deep autoencoder or a classifier on MNIST digits[Project]
Deep Learning 大牛Geoffrey E. Hinton's HomePage[Website]
Multiple Instance Logistic Discriminant-based Metric Learning (MildML) and Logistic Discriminant-based Metric Learning (LDML)[Code]
Sparse coding simulation software[Project]
Visual Recognition and Machine Learning Summer School[Software]

十一、目标、行为识别Object, Action Recognition：

Action Recognition by Dense Trajectories[Project][Code]
Action Recognition Using a Distributed Representation of Pose and Appearance[Project]
Recognition Using Regions[Paper][Code]
2D Articulated Human Pose Estimation[Project]
Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression[Paper][Code]
Estimating Human Pose from Occluded Images[Paper][Code]
Quasi-dense wide baseline matching[Project]
ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms[Project]
Real Time Head Pose Estimation with Random Regression Forests[Project]
2D Action Recognition Serves 3D Human Pose Estimation[
A Hough Transform-Based Voting Framework for Action Recognition[
Motion Interchange Patterns for Action Recognition in Unconstrained Videos[
2D articulated human pose estimation software[Project]
Learning and detecting shape models [code]
Progressive Search Space Reduction for Human Pose Estimation[Project]
Learning Non-Rigid 3D Shape from 2D Motion[Project]

十二、图像处理：

Distance Transforms of Sampled Functions[Project]
The Computer Vision Homepage[Project]
Efficient appearance distances between windows[code]
Image Exploration algorithm[code]
Motion Magnification 运动放大 [Project]
Bilateral Filtering for Gray and Color Images 双边滤波器 [Project]
A Fast Approximation of the Bilateral Filter using a Signal Processing Approach [

十三、一些实用工具：

EGT: a Toolbox for Multiple View Geometry and Visual Servoing[Project] [Code]
a development kit of matlab mex functions for OpenCV library[Project]
Fast Artificial Neural Network Library[Project]

十四、人手及指尖检测与识别：

finger-detection-and-gesture-recognition [Code]
Hand and Finger Detection using JavaCV[Project]
Hand and fingers detection[Code]

十五、场景解释：

Nonparametric Scene Parsing via Label Transfer [Project]

十六、光流Optical flow：

High accuracy optical flow using a theory for warping [Project]
Dense Trajectories Video Description [Project]
SIFT Flow: Dense Correspondence across Scenes and its Applications[Project]
KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker [Project]
Tracking Cars Using Optical Flow[Project]
Secrets of optical flow estimation and their principles[Project]
implmentation of the Black and Anandan dense optical flow method[Project]
Optical Flow Computation[Project]
Beyond Pixels: Exploring New Representations and Applications for Motion Analysis[Project]
A Database and Evaluation Methodology for Optical Flow[Project]
optical flow relative[Project]
Robust Optical Flow Estimation [Project]
optical flow[Project]

十七、图像检索Image Retrieval：

Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval [Paper][code]

十八、马尔科夫随机场Markov Random Fields：

Markov Random Fields for Super-Resolution [Project]
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors [Project]

十九、运动检测Motion detection：

Moving Object Extraction, Using Models or Analysis of Regions [Project]
Background Subtraction: Experiments and Improvements for ViBe [Project]
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications [Project]
changedetection.net: A new change detection benchmark dataset[Project]
ViBe - a powerful technique for background detection and subtraction in video sequences[Project]
Background Subtraction Program[Project]
Motion Detection Algorithms[Project]
Stuttgart Artificial Background Subtraction Dataset[Project]
Object Detection, Motion Estimation, and Tracking[Project]

Feature Detection and Description

General Libraries:
- VLFeat – Implementation of various feature descriptors (including SIFT, HOG, and LBP) and covariant feature detectors (including DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris). Easy-to-use Matlab interface. See Modern features: Software – Slides providing a demonstration of VLFeat and also links to other software. Check also VLFeat hands-on session training
- OpenCV – Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)
Fast Keypoint Detectors for Real-time Applications:
- FAST – High-speed corner detector implementation for a wide variety of platforms
- AGAST – Even faster than the FAST corner detector. A multi-scale version of this method is used for the BRISK descriptor (ECCV 2010).
Binary Descriptors for Real-Time Applications:
- BRIEF – C++ code for a fast and accurate interest point descriptor (not invariant to rotations and scale) (ECCV 2010)
- ORB – OpenCV implementation of the Oriented-Brief (ORB) descriptor (invariant to rotations, but not scale)
- BRISK – Efficient Binary descriptor invariant to rotations and scale. It includes a Matlab mex interface. (ICCV 2011)
- FREAK – Faster than BRISK (invariant to rotations and scale) (CVPR 2012)
SIFT and SURF Implementations:
- SIFT: VLFeat, OpenCV, Original code by David Lowe, GPU implementation, OpenSIFT
- SURF: Herbert Bay’s code, OpenCV, GPU-SURF
Other Local Feature Detectors and Descriptors:
- VGG Affine Covariant features – Oxford code for various affine covariant feature detectors and descriptors.
- LIOP descriptor – Source code for the Local Intensity order Pattern (LIOP) descriptor (ICCV 2011).
- Local Symmetry Features – Source code for matching of local symmetry features under large variations in lighting, age, and rendering style (CVPR 2012).
Global Image Descriptors:
- GIST – Matlab code for the GIST descriptor
- CENTRIST – Global visual descriptor for scene categorization and object detection (PAMI 2011)
Feature Coding and Pooling
- VGG Feature Encoding Toolkit – Source code for various state-of-the-art feature encoding methods – including Standard hard encoding, Kernel codebook encoding, Locality-constrained linear encoding, and Fisher kernel encoding.
- Spatial Pyramid Matching – Source code for feature pooling based on spatial pyramid matching (widely used for image classification)
Convolutional Nets and Deep Learning
- EBLearn – C++ Library for Energy-Based Learning. It includes several demos and step-by-step instructions to train classifiers based on convolutional neural networks.
- Torch7 – Provides a matlab-like environment for state-of-the-art machine learning algorithms, including a fast implementation of convolutional neural networks.
- Deep Learning - Various links for deep learning software.
Part-Based Models
- Deformable Part-based Detector – Library provided by the authors of the original paper (state-of-the-art in PASCAL VOC detection task)
- Efficient Deformable Part-Based Detector – Branch-and-Bound implementation for a deformable part-based detector.
- Accelerated Deformable Part Model – Efficient implementation of a method that achieves the exact same performance of deformable part-based detectors but with significant acceleration (ECCV 2012).
- Coarse-to-Fine Deformable Part Model – Fast approach for deformable object detection (CVPR 2011).
- Poselets – C++ and Matlab versions for object detection based on poselets.
- Part-based Face Detector and Pose Estimation – Implementation of a unified approach for face detection, pose estimation, and landmark localization (CVPR 2012).
  
  Attributes and Semantic Features
  - Relative Attributes – Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).
  - Object Bank – Implementation of object bank semantic features (NIPS 2010). See alsoActionBank
  - Classemes, Picodes, and Meta-class features – Software for extracting high-level image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).
  Large-Scale Learning
  - Additive Kernels – Source code for fast additive kernel SVM classifiers (PAMI 2013).
  - LIBLINEAR – Library for large-scale linear SVM classification.
  - VLFeat – Implementation for Pegasos SVM and Homogeneous Kernel map.
  Fast Indexing and Image Retrieval
  - FLANN – Library for performing fast approximate nearest neighbor.
  - Kernelized LSH – Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).
  - ITQ Binary codes – Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing (CVPR 2011).
  - INRIA Image Retrieval – Efficient code for state-of-the-art large-scale image retrieval (CVPR 2011).
  Object Detection
  - See Part-based Models and Convolutional Nets above.
  - Pedestrian Detection at 100fps – Very fast and accurate pedestrian detector (CVPR 2012).
  - Caltech Pedestrian Detection Benchmark – Excellent resource for pedestrian detection, with various links for state-of-the-art implementations.
  - OpenCV – Enhanced implementation of Viola&Jones real-time object detector, with trained models for face detection.
  - Efficient Subwindow Search – Source code for branch-and-bound optimization for efficient object localization (CVPR 2008).
  3D Recognition
  - Point-Cloud Library – Library for 3D image and point cloud processing.
  Action Recognition
  - ActionBank – Source code for action recognition based on the ActionBank representation (CVPR 2012).
  - STIP Features – software for computing space-time interest point descriptors
  - Independent Subspace Analysis – Look for Stacked ISA for Videos (CVPR 2011)
  - Velocity Histories of Tracked Keypoints - C++ code for activity recognition using the velocity histories of tracked keypoints (ICCV 2009)
  Datasets
  
  Attributes
  - Animals with Attributes – 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.
  - aYahoo and aPascal – Attribute annotations for images collected from Yahoo and Pascal VOC 2008.
  - FaceTracer – 15,000 faces annotated with 10 attributes and fiducial points.
  - PubFig – 58,797 face images of 200 people with 73 attribute classifier outputs.
  - [url=http://vis-www.cs.umass.edu/lfw/]LFW[/url] – 13,233 face images of 5,749 people with 73 attribute classifier outputs.
  - Human Attributes – 8,000 people with annotated attributes. Check also this link for another dataset of human attributes.
  - SUN Attribute Database – Large-scale scene attribute database with a taxonomy of 102 attributes.
  - ImageNet Attributes – Variety of attribute labels for the ImageNet dataset.
  - Relative attributes – Data for OSR and a subset of PubFig datasets. Check also this linkfor the WhittleSearch data.
  - Attribute Discovery Dataset – Images of shopping categories associated with textual descriptions.
  Fine-grained Visual Categorization
  - Caltech-UCSD Birds Dataset – Hundreds of bird categories with annotated parts and attributes.
  - Stanford Dogs Dataset – 20,000 images of 120 breeds of dogs from around the world.
  - Oxford-IIIT Pet Dataset – 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is included.
  - Leeds Butterfly Dataset – 832 images of 10 species of butterflies.
  - Oxford Flower Dataset – Hundreds of flower categories.
  Face Detection
  - [url=http://vis-www.cs.umass.edu/fddb/]FDDB[/url] – UMass face detection dataset and benchmark (5,000+ faces)
  - CMU/MIT – Classical face detection dataset.
  Face Recognition
  - Face Recognition Homepage – Large collection of face recognition datasets.
  - [url=http://vis-www.cs.umass.edu/lfw/]LFW[/url] – UMass unconstrained face recognition dataset (13,000+ face images).
  - NIST Face Homepage – includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.
  - CMU Multi-PIE – contains more than 750,000 images of 337 people, with 15 different views and 19 lighting conditions.
  - FERET – Classical face recognition dataset.
  - Deng Cai’s face dataset in Matlab Format – Easy to use if you want play with simple face datasets including Yale, ORL, PIE, and Extended Yale B.
  - SCFace – Low-resolution face dataset captured from surveillance cameras.
  Handwritten Digits
  - MNIST – large dataset containing a training set of 60,000 examples, and a test set of 10,000 examples.
  Pedestrian Detection
  - Caltech Pedestrian Detection Benchmark – 10 hours of video taken from a vehicle,350K bounding boxes for about 2.3K unique pedestrians.
  - INRIA Person Dataset – Currently one of the most popular pedestrian detection datasets.
  - ETH Pedestrian Dataset – Urban dataset captured from a stereo rig mounted on a stroller.
  - TUD-Brussels Pedestrian Dataset – Dataset with image pairs recorded in an crowded urban setting with an onboard camera.
  - PASCAL Human Detection – One of 20 categories in PASCAL VOC detection challenges.
  - USC Pedestrian Dataset – Small dataset captured from surveillance cameras.
  Generic Object Recognition
  - ImageNet – Currently the largest visual recognition dataset in terms of number of categories and images.
  - Tiny Images – 80 million 32x32 low resolution images.
  - Pascal VOC – One of the most influential visual recognition datasets.
  - Caltech 101 / Caltech 256 – Popular image datasets containing 101 and 256 object categories, respectively.
  - MIT LabelMe – Online annotation tool for building computer vision databases.
  Scene Recognition
  - MIT SUN Dataset – MIT scene understanding dataset.
  - UIUC Fifteen Scene Categories – Dataset of 15 natural scene categories.
  Feature Detection and Description
  - VGG Affine Dataset – Widely used dataset for measuring performance of feature detection and description. CheckVLBenchmarksfor an evaluation framework.
  Action Recognition
  - Benchmarking Activity Recognition – CVPR 2012 tutorial covering various datasets for action recognition.
  RGBD Recognition
  - RGB-D Object Dataset – Dataset containing 300 common household objects
  Reference:
  
  [1]: http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html
  
  特征提取
  - SURF特征: http://www.vision.ee.ethz.ch/software/index.de.html(当然这只是其中之一)
  - LBP特征(一种纹理特征)：http://www.comp.hkbu.edu.hk/~icpr06/tutorials/Pietikainen.html
  - Fast Corner Detection（OpenCV中的Fast算法）:FAST Corner Detection -- Edward Rosten
  机器视觉
  - A simple object detector with boosting(Awarded the Best Short Course Prize at ICCV 2005，So了解adaboost的推荐之作)：http://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.html
  - Boosting(该网页上有相当全的Boosting的文章和几个Boosting代码，本人推荐)：http://cbio.mskcc.org/~aarvey/boosting_papers.html
  - Adaboost Matlab 工具：http://graphics.cs.msu.ru/en/science/research/machinelearning/adaboosttoolbox
  - MultiBoost(不说啥了，多类Adaboost算法的程序)：http://sourceforge.net/projects/multiboost/
  - TextonBoost(我们教研室王冠夫师兄的毕设): Jamie Shotton - Code
  - LibSvm的老爹（推荐）: http://www.csie.ntu.edu.tw/~cjlin/
  - Conditional Random Fields（CRF论文+Code列表，推荐）
  - CRF++: Yet Another CRF toolkit
  - Conditional Random Field (CRF) Toolbox for Matlab
  - Tree CRFs
  - LingPipe: Installation
  - Hidden Markov Models（推荐）
  - 隐马尔科夫模型(Hidden Markov Models)系列之一 - eaglex的专栏 - 博客频道 - CSDN.NET（推荐）
  综合代码
  - CvPapers(好吧，牛吧网站，里面有ICCV，CVPR，ECCV，SIGGRAPH的论文收录，然后还有一些论文的代码搜集，要求加精！)：http://www.cvpapers.com/
  - Computer Vision Software(里面代码很多，并详细的给出了分类)：http://peipa.essex.ac.uk/info/software.html
  - 某人的Windows Live（我看里面东东不少就收藏了）：https://skydrive.live.com/?cid=3b6244088fd5a769#cid=3B6244088FD5A769&id=3B6244088FD5A769!523
  - MATLAB and Octave Functions for Computer Vision and Image Processing（这个里面的东西也很全，只是都是用Matlab和Octave开发的）：http://www.csse.uwa.edu.au/~pk/research/matlabfns/
  - Computer Vision Resources（里面的视觉算法很多，给出了相应的论文和Code，挺好的）：https://netfiles.uiuc.edu/jbhuang1/www/resources/vision/index.html
  - MATLAB Functions for Multiple View Geometry（关于物体多视角计算的库）：http://www.robots.ox.ac.uk/~vgg/hzbook/code/
  - Evolutive Algorithm based on Naïve Bayes models Estimation（单独列了一个算法的Code）：http://www.cvc.uab.cat/~xbaro/eanbe/#_Software
  主页代码
  - Pablo Negri's Home Page
  - Jianxin Wu's homepage
  - Peter Carbonetto
  - Markov Random Fields for Super-Resolution
  - Detecting and Sketching the Common
  - Pedro Felzenszwalb
  - Hae JONG, SEO
  - CAP 5416 - Computer Vision
  - Parallel Tracking and Mapping for Small AR Workspaces (PTAM)
  - Deva Ramanan - UC Irvine - Computer Vision
  - Raghuraman Gopalan
  - Hui Kong
  - Jamie Shotton - Post-Doctoral Researcher in Computer Vision
  - Jean-Yves AUDIBERT
  - Olga Veksler
  - Stephen Gould
  - Publications (Last Update: 09/30/10)
  - Karim Ali - FlowBoost
  - A simple parts and structure object detector
  - Code - Oxford Brookes Vision Group
  - Taku Kudo
  行人检测
  - Histogram of Oriented Gradient (Windows)
  - INRIA Pedestrian detector
  - Poselets
  - William Robson Schwartz - Softwares
  - calvin upper-body detector v1.02
  - RPT@CVG
  - Main Page
  - Source Code
  - Dr. Luciano Spinello
  - Pedestrian Detection
  - Class-Specific Hough Forests for Object Detection
  - Jianxin Wu's homepage（就是上面的）
  - Berkeley大学做的Pedestrian Detector，使用交叉核的支持向量机，特征使用HOG金字塔，提供Matlab和C++混编的代码：http://www.cs.berkeley.edu/~smaji/projects/ped-detector/
  视觉壁障
  - High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning
  - TLD(2010年很火的tracking算法)
  - online boosting trackers
  - Boris Babenko
  - Optical Flow Algorithm Evaluation (提供了一个动态贝叶斯网络框架，例如递归信息处理与分析、卡尔曼滤波、粒子滤波、序列蒙特卡罗方法等，C++写的)http://of-eval.sourceforge.net/
  物体检测算法
  - Object Detection
  - Software for object detection
  人脸检测
  - Source Code
  - 10个人脸检测项目
  - Jianxin Wu's homepage（又是这货）
  ICA独立成分分析
  - An ICA page-papers,code,demo,links (Tony Bell)
  - FastICA
  - Cached k-d tree search for ICP algorithms
  滤波算法
  - 卡尔曼滤波：The Kalman Filter(终极网页)
  - Bayesian Filtering Library: The Bayesian Filtering Library
  路面识别
  - Source Code
  - Vanishing point detection for general road detection
  分割算法
  - MATLAB Normalized Cuts Segmentation Code：software
  - 超像素分割：SLIC Superpixels
  ZZ： http://blog.sina.com.cn/s/blog_5086c3e20101kdy5.html，http://www.yuanyong.org/cv/cv-code-three.html

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