2013计算机视觉代码合集

http://www.yuanyong.org 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 also ActionBank 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 link for 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