From: http://www.cnblogs.com/einyboy/p/3594432.html
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 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 trainingOpenCV – 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 platformsAGAST – 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, OpenSIFTSURF: 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 descriptorCENTRIST – 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 ActionBankClassemes, 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 descriptorsIndependent 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.LFW – 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
FDDB – 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.LFW – 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. CheckVLBenchmarks for 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
