机器视觉开源代码集合

一、特征提取Feature Extraction：

• SIFT [1] [Demo program][SIFT Library] [VLFeat]
• PCASIFT [2] [Project]
• AffineSIFT [3] [Project]
• SURF [4] [OpenSURF] [Matlab Wrapper]
• Affine Covariant Features [5] [Oxford project]
• MSER [6] [Oxford project] [VLFeat]
• Geetric Blur [7] [Code]
• Local SelfSimilarity Descriptor [8] [Oxford implementation]
• Global and Efficient SelfSimilarity [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]
• SpaceTime Interest Points (STIP) [14][Project] [Code]
• Boundary Preserving Dense Local Regions [15][Project]
• Weighted Histogram[Code]
• Histogrambased 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 FASTER[Project]
• Realtime Facial Feature Detection using Conditional Regression Forests[Project]
• Global and Efficient SelfSimilarity for Object Classification and Detection[code]
• WαSH: Weighted αShapes 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 Graphbased Image Segmentation [3] [C++ code] [Matlab wrapper]
• MeanShift Image Segmentation [4] [EDISON C++ code] [Matlab wrapper]
• OWTUCM Hierarchical Segmentation [5] [Resources]
• Turbepixels [6] [Matlab code 32bit] [Matlab code 64bit] [Updated code]
• QuickShift [7] [VLFeat]
• SLIC Superpixels [8] [Project]
• Segmentation by Minimum Code Length [9] [Project]
• Biased Normalized Cut [10] [Project]
• Segmentation Tree [1112] [Project]
• Entropy Rate Superpixel Segmentation [13] [Code]
• Fast Approximate Energy Minimization via Graph Cuts[Paper][Code]
• Ef?cient Planar Graph Cuts with Applications in Cputer Vision[Paper][Code]
• Isoperimetric Graph Partitioning for Image Segmentation[Paper][Code]
• Rand Walks for Image Segmentation[Paper][Code]
• Bloss V: A new implementation of a minimum cost perfect matching algorithm[Code]
• An Experimental Cparison of MinCut/MaxFlow Algorithms for Energy Minimization in Cputer Vision[Paper][Code]
• Geodesic Star Convexity for Interactive Image Segmentation[Project]
• Contour Detection and Image Segmentation Resources[Project][Code]
• Biased Normalized Cuts[Project]
• Maxflow/mincut[Project]
• ChanVese Segmentation using Level Set[Project]
• A Toolbox of Level Set Methods[Project]
• Reinitialization Free Level Set Evolution via Reaction Diffusion[Project]
• Improved CV 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 EnergyDriven 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 RealTime Detection of TextureLess Objects: LineMOD [Project]
• Image Processing On Line[Project]
• Robust Optical Flow Estimation[Project]
• Where's Waldo: Matching People in Images of Crowds[Project]
• Scalable Multiclass Object Detection[Project]
• ClassSpecific Hough Forests for Object Detection[Project]
• Deformed Lattice Detection In RealWorld 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]
• Frequencytuned salient region detection [2] [Project]
• Saliency detection using maximum symmetric surround [3] [Project]
• Attention via Information Maximization [4] [Matlab code]
• Contextaware saliency detection [5] [Matlab code]
• Graphbased visual saliency [6] [Matlab code]
• Saliency detection: A spectral residual approach. [7] [Matlab code]
• Segmenting salient objects fr images and videos. [8] [Matlab code]
• Saliency Using Natural statistics. [9] [Matlab code]
• Discriminant Saliency for Visual Recognition fr 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]
• TopDown 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]
• Localityconstrained Linear Coding [3] [Project] [Matlab code]
• Sparse Coding [4] [Project] [Matlab code]
• Texture Classification [5] [Project]
• Multiple Kernels for Image Classification [6] [Project]
• Feature Cbination [7] [Project]
• SuperParsing [Code]
• Large Scale Correlation Clustering Optimization[Matlab code]
• Detecting and Sketching the Cmon[Project]
• SelfTuning Spectral Clustering[Project][Code]
• User Assisted Separation of Reflections fr 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]
• Learningbased 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]
• Realtime Cpressive Tracking[Project]
• Robust Object Tracking via Sparsitybased 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]
• Cpressive Sensing Resources[Project]
• Robust RealTime Visual Tracking using PixelWise Posteriors[Project]
• TrackingLearningDetection[Project][OpenTLD/C++ Code]
• the HandVu：visionbased hand gesture interface[Project]
• Learning Probabilistic NonLinear Latent Variable Models for Tracking Cplex 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 Fr Shading Using Linear Approximation[Code]
• Cbining Shape fr Shading and Stereo Depth Maps[Project][Code]
• Shape fr Shading: A Survey[Paper][Code]
• A SpatioTemporal Descriptor based on 3D Gradients (HOG3D)[Project][Code]
• Multicamera Scene Reconstruction via Graph Cuts[Paper][Code]
• A Fast Marching Formulation of Perspective Shape fr 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 3D Scene Structure fr a Single Still Image[Project]

十、机器学习算法：

• Matlab class for cputing Approximate Nearest Nieghbor (ANN) [Matlab classproviding interface toANN library]
• Rand Sampling[code]
• Probabilistic Latent Semantic Analysis (pLSA)[Code]
• FASTANN and FASTCLUSTER for approximate kmeans (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 LevenbergMarquardt 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]
• LeNet5, convolutional neural networks[Project]
• Training a deep autoencoder or a classifier on MNIST digits[Project]
• Deep Learning 大牛Geoffrey E. Hinton's HePage[Website]
• Multiple Instance Logistic Discriminantbased Metric Learning (MildML) and Logistic Discriminantbased 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 MultiDimensional Boosting Regression[Paper][Code]
• Estimating Human Pose fr Occluded Images[Paper][Code]
• Quasidense wide baseline matching[Project]
• ChaLearn Gesture Challenge:Principal motion: PCAbased reconstruction of motion histograms[Project]
• Real Time Head Pose Estimation with Rand Regression Forests[Project]
• 2D Action Recognition Serves 3D Human Pose Estimation[Project]
• A Hough TransformBased 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 NonRigid 3D Shape fr 2D Motion[Project]

十二、图像处理：

• Distance Transforms of Sampled Functions[Project]
• The Cputer Vision Hepage[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 Geetry 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：

• fingerdetectionandgesturerecognition[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 KanadeLucasTasi 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 Cputation[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：

• SemiSupervised Distance Metric Learning for Collaborative Image Retrieval[Paper][code]

十八、马尔科夫随机场Markov Rand Fields：

• Markov Rand Fields for SuperResolution[Project]
• A Cparative Study of Energy Minimization Methods for Markov Rand Fields with SmoothnessBased 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 SelfOrganizing Approach to Background Subtraction for Visual Surveillance Applications [Project]
• changedetection: 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). Easytouse Matlab interface. SeeModern features: Software– Slides providing a demonstration of VLFeat and also links to other software. Check alsoVLFeat handson session training
• OpenCV– Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)

Fast Keypoint Detectors for Realtime Applications:

• FAST– Highspeed corner detector implementation for a wide variety of platforms
• AGAST– Even faster than the FAST corner detector. A multiscale version of this method is used for the BRISK descriptor (ECCV 2010).

Binary Descriptors for RealTime 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 OrientedBrief (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 codeby David Lowe,GPU implementation,OpenSIFT
• SURF:Herbert Bay’s code,OpenCV,GPUSURF

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 stateoftheart feature encoding methods – including Standard hard encoding, Kernel codebook encoding, Localityconstrained 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 EnergyBased Learning. It includes several demos and stepbystep instructions to train classifiers based on convolutional neural networks.
• Torch7– Provides a matlablike environment for stateoftheart machine learning algorithms, including a fast implementation of convolutional neural networks.
• Deep Learning Various links for deep learning software.

PartBased Models

• Deformable Partbased Detector– Library provided by the authors of the original paper (stateoftheart in PASCAL VOC detection task)
• Efficient Deformable PartBased Detector– BranchandBound implementation for a deformable partbased detector.
• Accelerated Deformable Part Model– Efficient implementation of a method that achieves the exact same performance of deformable partbased detectors but with significant acceleration (ECCV 2012).
• CoarsetoFine Deformable Part Model– Fast approach for deformable object detection (CVPR 2011).
• Poselets– C++ and Matlab versions for object detection based on poselets.
• Partbased Face Detector and Pose Estimation– Implementation of a unified approach for face detection, pose estimation, and landmark localization (CVPR 2012).

Attributes and Semantic Features

• Relative Attributes– Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).
• Object Bank– Implementation of object bank semantic features (NIPS 2010). See alsoActionBank
• Classemes, Picodes, and Metaclass features– Software for extracting highlevel image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).

LargeScale Learning

• Additive Kernels– Source code for fast additive kernel SVM classifiers (PAMI 2013).
• LIBLINEAR– Library for largescale linear SVM classification.
• VLFeat– Implementation for Pegasos SVM and Hogeneous Kernel map.

Fast Indexing and Image Retrieval

• FLANN– Library for performing fast approximate nearest neighbor.
• Kernelized LSH– Source code for Kernelized LocalitySensitive Hashing (ICCV 2009).
• ITQ Binary codes– Code for generation of small binary codes using Iterative Quantization and other baselines such as LocalitySensitiveHashing (CVPR 2011).
• INRIA Image Retrieval– Efficient code for stateoftheart largescale image retrieval (CVPR 2011).

Object Detection

• SeePartbased ModelsandConvolutional Netsabove.
• 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 stateoftheart implementations.
• OpenCV– Enhanced implementation of Viola&Jones realtime object detector, with trained models for face detection.
• Efficient Subwindow Search– Source code for branchandbound optimization for efficient object localization (CVPR 2008).

3D Recognition

• PointCloud 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 cputing spacetime 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)

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Datasets

Attributes

• Animals with Attributes– 30,475 images of 50 animals classes with 6 preextracted feature representations for each image.
• aYahoo and aPascal– Attribute annotations for images collected fr 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 thislinkfor another dataset of human attributes.
• SUN Attribute Database– Largescale scene attribute database with a taxony 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 thislinkfor the WhittleSearch data.
• Attribute Discovery Dataset– Images of shopping categories associated with textual descriptions.

Finegrained Visual Categorization

• CaltechUCSD Birds Dataset– Hundreds of bird categories with annotated parts and attributes.
• Stanford Dogs Dataset– 20,000 images of 120 breeds of dogs fr around the world.
• OxfordIIIT 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 Hepage– Large collection of face recognition datasets.
• LFW– UMass unconstrained face recognition dataset (13,000+ face images).
• NIST Face Hepage– includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.
• CMU MultiPIE– 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– Lowresolution face dataset captured fr 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 fr 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 fr a stereo rig mounted on a stroller.
• TUDBrussels 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 fr 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 cputer 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

• RGBD Object Dataset– Dataset containing 300 cmon household objects

Reference:

[1]:rogerioferis/VisualRecognitionAndSearch/Resources

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