计算机视觉、机器学习相关领域论文和源代码大集合--持续更新……

注：文章转自http://blog.csdn.net/zouxy09/article/details/8550952

计算机视觉、机器学习相关领域论文和源代码大集合--持续更新……

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http://blog.csdn.net/zouxy09

 

注：下面有project网站的大部分都有paper和相应的code。Code一般是C/C++或者Matlab代码。

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[Project]

·           A Hough Transform-Based Voting Framework for Action Recognition[Project]

·           Motion Interchange Patterns for Action Recognition in Unconstrained Videos[Project]

·         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 [Project]

                  

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