Topic |
Resources |
References |
Feature Extraction |
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Image Segmentation |
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Object Detection |
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Saliency Detection |
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Image Classification |
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Category-Independent Object Proposal |
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MRF |
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Shadow Detection |
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Optical Flow |
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Object Tracking |
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Image Matting |
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Bilateral Filtering |
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Image Denoising |
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Image Super-Resolution |
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Image Deblurring |
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Image Quality Assessment |
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Density Estimation |
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Dimension Reduction |
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Sparse Coding |
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Low-Rank Matrix Completion |
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Nearest Neighbors matching |
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Steoreo |
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Structure from motion |
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Distance Transformation |
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Chamfer Matching |
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Clustering |
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Classification |
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Regression |
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Multiple Kernel Learning (MKL) |
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Multiple Instance Learning (MIL) |
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Other Utilities |
Useful Links (dataset, lectures, and other softwares)
| Conference Information |
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| Papers |
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| Datasets |
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| Lectures |
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| Source Codes |
一、特征提取Feature Extraction：
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SIFT [1] [Demo program][SIFT Library] [VLFeat]
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PCA-SIFT [2] [Project]
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Affine-SIFT [3] [Project]
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SURF [4] [OpenSURF] [Matlab Wrapper]
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Affine Covariant Features [5] [Oxford project]
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MSER [6] [Oxford project] [VLFeat]
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Geometric Blur [7] [Code]
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Local Self-Similarity Descriptor [8] [Oxford implementation]
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Global and Efficient Self-Similarity [9] [Code]
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Histogram of Oriented Graidents [10] [INRIA Object Localization Toolkit] [OLT toolkit for Windows]
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GIST [11] [Project]
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Shape Context [12] [Project]
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Color Descriptor [13] [Project]
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Pyramids of Histograms of Oriented Gradients [Code]
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Boundary Preserving Dense Local Regions [15][Project]
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Weighted Histogram[Code]
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An OpenCV - C++ implementation of Local Self Similarity Descriptors [Project]
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Fast Sparse Representation with Prototypes[Project]
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Corner Detection [Project]
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AGAST Corner Detector: faster than FAST and even FAST-ER[Project]
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Real-time Facial Feature Detection using Conditional Regression Forests[Project]
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Global and Efficient Self-Similarity for Object Classification and Detection[code]
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WαSH: Weighted α-Shapes for Local Feature Detection[Project]
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HOG[Project]
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Online Selection of Discriminative Tracking Features[Project]
二、图像分割Image Segmentation：
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Normalized Cut [1] [Matlab code]
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Gerg Mori’ Superpixel code [2] [Matlab code]
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Efficient Graph-based Image Segmentation [3] [C++ code] [Matlab wrapper]
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Mean-Shift Image Segmentation [4] [EDISON C++ code] [Matlab wrapper]
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OWT-UCM Hierarchical Segmentation [5] [Resources]
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Turbepixels [6] [Matlab code 32bit] [Matlab code 64bit] [Updated code]
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Quick-Shift [7] [VLFeat]
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SLIC Superpixels [8] [Project]
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Segmentation by Minimum Code Length [9] [Project]
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Biased Normalized Cut [10] [Project]
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Segmentation Tree [11-12] [Project]
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Entropy Rate Superpixel Segmentation [13] [Code]
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Fast Approximate Energy Minimization via Graph Cuts[Paper][Code]
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Efficient Planar Graph Cuts with Applications in Computer Vision[Paper][Code]
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Isoperimetric Graph Partitioning for Image Segmentation[Paper][Code]
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Blossom V: A new implementation of a minimum cost perfect matching algorithm[Code]
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An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision[Paper][Code]
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Geodesic Star Convexity for Interactive Image Segmentation[Project]
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Contour Detection and Image Segmentation Resources[Project][Code]
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Biased Normalized Cuts[Project]
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Max-flow/min-cut[Project]
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Chan-Vese Segmentation using Level Set[Project]
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A Toolbox of Level Set Methods[Project]
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Re-initialization Free Level Set Evolution via Reaction Diffusion[Project]
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A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction[Paper][Code]
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Level Set Method Research by Chunming Li[Project]
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ClassCut for Unsupervised Class Segmentation[code]
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SEEDS: Superpixels Extracted via Energy-Driven Sampling [Project][other]
三、目标检测Object Detection：
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A simple object detector with boosting [Project]
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INRIA Object Detection and Localization Toolkit [1] [Project]
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Discriminatively Trained Deformable Part Models [2] [Project]
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Cascade Object Detection with Deformable Part Models [3] [Project]
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Poselet [4] [Project]
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Implicit Shape Model [5] [Project]
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Viola and Jones’s Face Detection [6] [Project]
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Bayesian Modelling of Dyanmic Scenes for Object Detection[Paper][Code]
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Hand detection using multiple proposals[Project]
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Color Constancy, Intrinsic Images, and Shape Estimation[Paper][Code]
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Discriminatively trained deformable part models[Project]
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Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD [Project]
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Image Processing On Line[Project]
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Robust Optical Flow Estimation[Project]
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Where's Waldo: Matching People in Images of Crowds[Project]
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Scalable Multi-class Object Detection[Project]
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Class-Specific Hough Forests for Object Detection[Project]
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Deformed Lattice Detection In Real-World Images[Project]
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Discriminatively trained deformable part models[Project]
四、显著性检测Saliency Detection：
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Itti, Koch, and Niebur’ saliency detection [1] [Matlab code]
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Frequency-tuned salient region detection [2] [Project]
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Saliency detection using maximum symmetric surround [3] [Project]
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Attention via Information Maximization [4] [Matlab code]
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Context-aware saliency detection [5] [Matlab code]
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Graph-based visual saliency [6] [Matlab code]
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Saliency detection: A spectral residual approach. [7] [Matlab code]
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Segmenting salient objects from images and videos. [8] [Matlab code]
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Saliency Using Natural statistics. [9] [Matlab code]
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Discriminant Saliency for Visual Recognition from Cluttered Scenes. [10] [Code]
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Learning to Predict Where Humans Look [11] [Project]
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Global Contrast based Salient Region Detection [12] [Project]
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Bayesian Saliency via Low and Mid Level Cues[Project]
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Top-Down Visual Saliency via Joint CRF and Dictionary Learning[Paper][Code]
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Saliency Detection: A Spectral Residual Approach[Code]
五、图像分类、聚类Image Classification, Clustering
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Pyramid Match [1] [Project]
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Spatial Pyramid Matching [2] [Code]
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Locality-constrained Linear Coding [3] [Project] [Matlab code]
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Sparse Coding [4] [Project] [Matlab code]
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Texture Classification [5] [Project]
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Multiple Kernels for Image Classification [6] [Project]
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Feature Combination [7] [Project]
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SuperParsing [Code]
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Large Scale Correlation Clustering Optimization[Matlab code]
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Detecting and Sketching the Common[Project]
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User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior[Paper][Code]
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Filters for Texture Classification[Project]
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Multiple Kernel Learning for Image Classification[Project]
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SLIC Superpixels[Project]
六、抠图Image Matting
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A Closed Form Solution to Natural Image Matting [Code]
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Spectral Matting [Project]
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Learning-based Matting [Code]
七、目标跟踪Object Tracking：
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A Forest of Sensors - Tracking Adaptive Background Mixture Models [Project]
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Object Tracking via Partial Least Squares Analysis[Paper][Code]
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Robust Object Tracking with Online Multiple Instance Learning[Paper][Code]
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Online Visual Tracking with Histograms and Articulating Blocks[Project]
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Incremental Learning for Robust Visual Tracking[Project]
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Real-time Compressive Tracking[Project]
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Robust Object Tracking via Sparsity-based Collaborative Model[Project]
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Visual Tracking via Adaptive Structural Local Sparse Appearance Model[Project]
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Online Discriminative Object Tracking with Local Sparse Representation[Paper][Code]
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Superpixel Tracking[Project]
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Learning Hierarchical Image Representation with Sparsity, Saliency and Locality[Paper][Code]
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Visual Tracking with Online Multiple Instance Learning[Project]
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Object detection and recognition[Project]
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Compressive Sensing Resources[Project]
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Robust Real-Time Visual Tracking using Pixel-Wise Posteriors[Project]
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Tracking-Learning-Detection[Project][OpenTLD/C++ Code]
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the HandVu：vision-based hand gesture interface[Project]
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Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities[Project]
八、Kinect：
九、3D相关：
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Shape From Shading Using Linear Approximation[Code]
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Combining Shape from Shading and Stereo Depth Maps[Project][Code]
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A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)[Project][Code]
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Multi-camera Scene Reconstruction via Graph Cuts[Paper][Code]
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A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination[Paper][Code]
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Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture[Project]
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Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers[Code]
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Learning 3-D Scene Structure from a Single Still Image[Project]
十、机器学习算法：
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Matlab class for computing Approximate Nearest Nieghbor (ANN) [Matlab class providing interface toANN library]
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Random Sampling[code]
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Probabilistic Latent Semantic Analysis (pLSA)[Code]
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FASTANN and FASTCLUSTER for approximate k-means (AKM)[Project]
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Fast Intersection / Additive Kernel SVMs[Project]
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SVM[Code]
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Ensemble learning[Project]
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Deep Learning[Net]
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Deep Learning Methods for Vision[Project]
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Neural Network for Recognition of Handwritten Digits[Project]
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Training a deep autoencoder or a classifier on MNIST digits[Project]
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THE MNIST DATABASE of handwritten digits[Project]
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Ersatz：deep neural networks in the cloud[Project]
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Deep Learning [Project]
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sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++[Project]
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Weka 3: Data Mining Software in Java[Project]
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Invited talk "A Tutorial on Deep Learning" by Dr. Kai Yu (余凯)[Video]
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CNN - Convolutional neural network class[Matlab Tool]
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Yann LeCun's Publications[Wedsite]
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LeNet-5, convolutional neural networks[Project]
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Training a deep autoencoder or a classifier on MNIST digits[Project]
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Deep Learning 大牛Geoffrey E. Hinton's HomePage[Website]
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Multiple Instance Logistic Discriminant-based Metric Learning (MildML) and Logistic Discriminant-based Metric Learning (LDML)[Code]
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Sparse coding simulation software[Project]
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Visual Recognition and Machine Learning Summer School[Software]
十一、目标、行为识别Object, Action Recognition：
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Action Recognition Using a Distributed Representation of Pose and Appearance[Project]
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2D Articulated Human Pose Estimation[Project]
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Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression[Paper][Code]
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Quasi-dense wide baseline matching[Project]
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ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms[Project]
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Real Time Head Pose Estimation with Random Regression Forests[Project]
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2D Action Recognition Serves 3D Human Pose Estimation[
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A Hough Transform-Based Voting Framework for Action Recognition[
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Motion Interchange Patterns for Action Recognition in Unconstrained Videos[
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2D articulated human pose estimation software[Project]
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Learning and detecting shape models [code]
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Progressive Search Space Reduction for Human Pose Estimation[Project]
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Learning Non-Rigid 3D Shape from 2D Motion[Project]
十二、图像处理：
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Distance Transforms of Sampled Functions[Project]
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The Computer Vision Homepage[Project]
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Efficient appearance distances between windows[code]
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Image Exploration algorithm[code]
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Motion Magnification 运动放大 [Project]
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Bilateral Filtering for Gray and Color Images 双边滤波器 [Project]
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A Fast Approximation of the Bilateral Filter using a Signal Processing Approach [
十三、一些实用工具：
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EGT: a Toolbox for Multiple View Geometry and Visual Servoing[Project] [Code]
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a development kit of matlab mex functions for OpenCV library[Project]
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Fast Artificial Neural Network Library[Project]
十四、人手及指尖检测与识别：
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finger-detection-and-gesture-recognition [Code]
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Hand and Finger Detection using JavaCV[Project]
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Hand and fingers detection[Code]
十五、场景解释：
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Nonparametric Scene Parsing via Label Transfer [Project]
十六、光流Optical flow：
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High accuracy optical flow using a theory for warping [Project]
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Dense Trajectories Video Description [Project]
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SIFT Flow: Dense Correspondence across Scenes and its Applications[Project]
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KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker [Project]
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Tracking Cars Using Optical Flow[Project]
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Secrets of optical flow estimation and their principles[Project]
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implmentation of the Black and Anandan dense optical flow method[Project]
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Optical Flow Computation[Project]
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Beyond Pixels: Exploring New Representations and Applications for Motion Analysis[Project]
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A Database and Evaluation Methodology for Optical Flow[Project]
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optical flow relative[Project]
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Robust Optical Flow Estimation [Project]
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optical flow[Project]
十七、图像检索Image Retrieval：
十八、马尔科夫随机场Markov Random Fields：
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A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors [Project]
十九、运动检测Motion detection：
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Moving Object Extraction, Using Models or Analysis of Regions [Project]
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Background Subtraction: Experiments and Improvements for ViBe [Project]
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A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications [Project]
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changedetection.net: A new change detection benchmark dataset[Project]
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ViBe - a powerful technique for background detection and subtraction in video sequences[Project]
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Background Subtraction Program[Project]
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Motion Detection Algorithms[Project]
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Stuttgart Artificial Background Subtraction Dataset[Project]
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Object Detection, Motion Estimation, and Tracking[Project]
Feature Detection and Description
General Libraries:
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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
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OpenCV – Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)
Fast Keypoint Detectors for Real-time Applications:
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FAST – High-speed corner detector implementation for a wide variety of platforms
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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:
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BRIEF – C++ code for a fast and accurate interest point descriptor (not invariant to rotations and scale) (ECCV 2010)
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ORB – OpenCV implementation of the Oriented-Brief (ORB) descriptor (invariant to rotations, but not scale)
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BRISK – Efficient Binary descriptor invariant to rotations and scale. It includes a Matlab mex interface. (ICCV 2011)
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FREAK – Faster than BRISK (invariant to rotations and scale) (CVPR 2012)
SIFT and SURF Implementations:
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SIFT: VLFeat, OpenCV, Original code by David Lowe, GPU implementation, OpenSIFT
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SURF: Herbert Bay’s code, OpenCV, GPU-SURF
Other Local Feature Detectors and Descriptors:
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VGG Affine Covariant features – Oxford code for various affine covariant feature detectors and descriptors.
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LIOP descriptor – Source code for the Local Intensity order Pattern (LIOP) descriptor (ICCV 2011).
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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:
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GIST – Matlab code for the GIST descriptor
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CENTRIST – Global visual descriptor for scene categorization and object detection (PAMI 2011)
Feature Coding and Pooling
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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.
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Spatial Pyramid Matching – Source code for feature pooling based on spatial pyramid matching (widely used for image classification)
Convolutional Nets and Deep Learning
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EBLearn – C++ Library for Energy-Based Learning. It includes several demos and step-by-step instructions to train classifiers based on convolutional neural networks.
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Torch7 – Provides a matlab-like environment for state-of-the-art machine learning algorithms, including a fast implementation of convolutional neural networks.
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Deep Learning - Various links for deep learning software.
Part-Based Models
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Deformable Part-based Detector – Library provided by the authors of the original paper (state-of-the-art in PASCAL VOC detection task)
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Efficient Deformable Part-Based Detector – Branch-and-Bound implementation for a deformable part-based detector.
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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).
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Coarse-to-Fine Deformable Part Model – Fast approach for deformable object detection (CVPR 2011).
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Poselets – C++ and Matlab versions for object detection based on poselets.
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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
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Relative Attributes – Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).
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Object Bank – Implementation of object bank semantic features (NIPS 2010). See also ActionBank
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Classemes, Picodes, and Meta-class features – Software for extracting high-level image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).
Large-Scale Learning
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Additive Kernels – Source code for fast additive kernel SVM classifiers (PAMI 2013).
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LIBLINEAR – Library for large-scale linear SVM classification.
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VLFeat – Implementation for Pegasos SVM and Homogeneous Kernel map.
Fast Indexing and Image Retrieval
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FLANN – Library for performing fast approximate nearest neighbor.
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Kernelized LSH – Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).
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ITQ Binary codes – Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing (CVPR 2011).
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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.
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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.
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OpenCV – Enhanced implementation of Viola&Jones real-time object detector, with trained models for face detection.
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Efficient Subwindow Search – Source code for branch-and-bound optimization for efficient object localization (CVPR 2008).
3D Recognition
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Point-Cloud Library – Library for 3D image and point cloud processing.
Action Recognition
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ActionBank – Source code for action recognition based on the ActionBank representation (CVPR 2012).
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STIP Features – software for computing space-time interest point descriptors
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Independent Subspace Analysis – Look for Stacked ISA for Videos (CVPR 2011)
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Velocity Histories of Tracked Keypoints - C++ code for activity recognition using the velocity histories of tracked keypoints (ICCV 2009)
Datasets
Attributes
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Animals with Attributes – 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.
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aYahoo and aPascal – Attribute annotations for images collected from Yahoo and Pascal VOC 2008.
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FaceTracer – 15,000 faces annotated with 10 attributes and fiducial points.
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PubFig – 58,797 face images of 200 people with 73 attribute classifier outputs.
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[url=http://vis-www.cs.umass.edu/lfw/]LFW[/url] – 13,233 face images of 5,749 people with 73 attribute classifier outputs.
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Human Attributes – 8,000 people with annotated attributes. Check also this link for another dataset of human attributes.
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SUN Attribute Database – Large-scale scene attribute database with a taxonomy of 102 attributes.
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ImageNet Attributes – Variety of attribute labels for the ImageNet dataset.
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Relative attributes – Data for OSR and a subset of PubFig datasets. Check also this link for the WhittleSearch data.
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Attribute Discovery Dataset – Images of shopping categories associated with textual descriptions.
Fine-grained Visual Categorization
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Caltech-UCSD Birds Dataset – Hundreds of bird categories with annotated parts and attributes.
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Stanford Dogs Dataset – 20,000 images of 120 breeds of dogs from around the world.
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Oxford-IIIT Pet Dataset – 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is included.
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Leeds Butterfly Dataset – 832 images of 10 species of butterflies.
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Oxford Flower Dataset – Hundreds of flower categories.
Face Detection
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[url=http://vis-www.cs.umass.edu/fddb/]FDDB[/url] – UMass face detection dataset and benchmark (5,000+ faces)
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CMU/MIT – Classical face detection dataset.
Face Recognition
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Face Recognition Homepage – Large collection of face recognition datasets.
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[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.
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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
-
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
-
Conditional Random Fields（CRF论文+Code列表，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）
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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/
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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
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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/
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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
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Jianxin Wu's homepage（就是上面的）
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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/
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High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning
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TLD(2010年很火的tracking算法)
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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/
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卡尔曼滤波：The Kalman Filter(终极网页)
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Bayesian Filtering Library: The Bayesian Filtering Library
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MATLAB Normalized Cuts Segmentation Code：software
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超像素分割：SLIC Superpixels
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以上是从下面网址中汇总来的：
http://www.360doc.com/content/12/0201/11/8703626_183332994.shtml
https://www.cnblogs.com/findumars/p/5009003.html
另外，在http://blog.csdn.net/zouxy09/article/details/8550952里也给出了一些项目链接汇总。