计算机视觉代码合集.docx

计算机视觉算法与代码集锦计算机视觉是结合了传统摄影测量，现代计算机信息技术、人工智能等多学科的一个大学科，是一片开垦不足的大陆，路很远，但很多人都在跋涉！本文转自CSDN（地址/whucv/article/details/7907391），是一篇很好的算法与代码总结文档，转载在此供大家学习参考。原文如下：UIUC的Jia-Bin Huang同学收集了很多计算机视觉方面的代码，链接如下：/jbhuang1/www/resources/vision/index.html248itemTopicNameReferenceLinkFeature Detection,Feature Extraction, and Action RecognitionSpace-Time Interest Points (STIP)I. Laptev, On Space-Time Interest Points, IJCV, 2005 and I. Laptev and T. Lindeberg, On Space-Time Interest Points, IJCV 2005http:/www.irisa.fr/vista/Equipe/People/Laptev/download/stip-1.1-winlinux.zipandhttp:/www.nada.kth.se/cvap/abstracts/cvap284.htmlAction Recognition3D Gradients (HOG3D)A. Klaser, M. Marszaek, and C. Schmid, BMVC, 2008.http:/lear.inrialpes.fr/people/klaeser/research_hog3dAction RecognitionDense Trajectories Video DescriptionH. Wang and A. Klaser and C. Schmid and C.- L. Liu, Action Recognition by Dense Trajectories, CVPR, 2011http:/lear.inrialpes.fr/people/wang/dense_trajectoriesAlpha MattingSpectral MattingA. Levin, A. Rav-Acha, D. Lischinski. Spectral Matting. PAMI 2008http:/www.vision.huji.ac.il/SpectralMatting/Alpha MattingShared MattingE. S. L. Gastal and M. M. Oliveira, Computer Graphics Forum, 2010http:/www.inf.ufrgs.br/eslgastal/SharedMatting/Alpha MattingBayesian MattingY. Y. Chuang, B. Curless, D. H. Salesin, and R. Szeliski, A Bayesian Approach to Digital Matting, CVPR, 2001http:/www1.idc.ac.il/toky/CompPhoto-09/Projects/Stud_projects/Miki/index.htmlAlpha MattingClosed Form MattingA. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting, PAMI 2008./alevin/matting.tar.gzAlpha MattingLearning-based MattingY. Zheng and C. Kambhamettu, Learning Based Digital Matting, ICCV 2009/matlabcentral/fileexchange/31412Camera CalibrationCamera Calibration Toolbox for Matlab/bouguetj/calib_doc/htmls/ref.html/bouguetj/calib_doc/Camera CalibrationEasyCamCalibJ. Barreto, J. Roquette, P. Sturm, and F. Fonseca, Automatic camera calibration applied to medical endoscopy, BMVC, 2009http:/arthronav.isr.uc.pt/easycamcalib/Camera CalibrationEpipolar Geometry ToolboxG.L. Mariottini, D. Prattichizzo, EGT: a Toolbox for Multiple View Geometry and Visual Servoing, IEEE Robotics & Automation Magazine, 2005http:/egt.dii.unisi.it/ClusteringSpectral Clustering - UW Project/spectral/ClusteringSpectral Clustering - UCSD Project/sagarwal/spectral-0.2.tgzClusteringSelf-Tuning Spectral Clustering/lihi/Demos/SelfTuningClustering.htmlClusteringK-Means - Oxford Code/vision/Code/vggkmeans.zipClusteringK-Means - VLFeat/Common Visual Pattern DiscoverySketching the CommonS. Bagon, O. Brostovsky, M. Galun and M. Irani, Detecting and Sketching the Common, CVPR 2010http:/www.wisdom.weizmann.ac.il/bagon/matlab_code/SketchCommonCVPR10_v1.1.tar.gzCommon Visual Pattern DiscoveryCommon Visual Pattern Discovery via Spatially Coherent CorrespondencesH. Liu, S. Yan, Common Visual Pattern Discovery via Spatially Coherent Correspondences, CVPR 2010/site/lhrbss/home/papers/SimplifiedCode.zip?attredirects=0Density EstimationKernel Density Estimation Toolbox/ihler/code/kde.htmlDepth SensorKinect SDK/en-us/kinectforwindows//en-us/kinectforwindows/Dimension ReductionISOMAP/Dimension ReductionLLE/roweis/lle/code.htmlDimension ReductionLaplacian Eigenmaps/mbelkin/algorithms/Laplacian.tarDimension ReductionDiffusion maps/annlee/software.htmDimension ReductionDimensionality Reduction Toolboxhttp:/homepage.tudelft.nl/19j49/Matlab_Toolbox_for_Dimensionality_Reduction.htmlDistance Metric LearningMatlab Toolkit for Distance Metric Learning/liuy/distlearn.htmDistance TransformationDistance Transforms of Sampled Functions/pff/dt/Feature DetectionCanny Edge DetectionJ. Canny, A Computational Approach To Edge Detection, PAMI, 1986/help/toolbox/images/ref/edge.htmlFeature DetectionFAST Corner DetectionE. Rosten and T. Drummond, Machine learning for high-speed corner detection, ECCV, 2006/work/fast.htmlFeature DetectionEdge Foci Interest PointsL. Zitnickand K. Ramnath, Edge Foci Interest Points, ICCV, 2011/en-us/um/people/larryz/edgefoci/edge_foci.htmFeature DetectionBoundary Preserving Dense Local RegionsJ. Kim and K. Grauman, Boundary Preserving Dense Local Regions, CVPR 2011/projects/bplr/bplr.htmlFeature ExtractionBRIEF: Binary Robust Independent Elementary FeaturesM. Calonder, V. Lepetit, C. Strecha, P. Fua, BRIEF: Binary Robust Independent Elementary Features, ECCV 2010http:/cvlab.epfl.ch/research/detect/brief/Feature Detection andFeature ExtractionScale-invariant feature transform (SIFT) - VLFeatD. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004./Feature Detection andFeature ExtractionScale-invariant feature transform (SIFT) - Demo SoftwareD. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004.http:/www.cs.ubc.ca/lowe/keypoints/Feature ExtractionGlobal and Efficient Self-SimilarityT. Deselaers and V. Ferrari. Global and Efficient Self-Similarity for Object Classification and Detection. CVPR 2010and T. Deselaers, V. Ferrari, Global and Efficient Self-Similarity for Object Classification and Detection, CVPR 2010http:/www.vision.ee.ethz.ch/calvin/gss/selfsim_release1.0.tgzFeature Detection andFeature ExtractionAffine-SIFTJ.M. Morel and G.Yu, ASIFT, A new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences, 2009http:/www.ipol.im/pub/algo/my_affine_sift/Feature Detection andFeature ExtractionGeometric BlurA. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. CVPR, 2005http:/www.robots.ox.ac.uk/vgg/software/MKL/Feature ExtractionPCA-SIFTY. Ke and R. Sukthankar, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors,CVPR, 2004/yke/pcasift/Feature Detection andFeature ExtractionScale-invariant feature transform (SIFT) - LibraryD. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004./hess/code/sift/Feature Detection andFeature ExtractionGroups of Adjacent Contour SegmentsV. Ferrari, L. Fevrier, F. Jurie, and C. Schmid, Groups of Adjacent Contour Segments for Object Detection, PAMI, 2007http:/www.robots.ox.ac.uk/vgg/share/ferrari/release-kas-v102.tgzFeature Detection andFeature ExtractionSpeeded Up Robust Feature (SURF) - Matlab WrapperH. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006http:/www.maths.lth.se/matematiklth/personal/petter/surfmex.phpFeature ExtractionShape ContextS. Belongie, J. Malik and J. Puzicha. Shape matching and object recognition using shape contexts, PAMI, 2002/Research/Projects/CS/vision/shape/sc_digits.htmlFeature Detection andFeature ExtractionSpeeded Up Robust Feature (SURF) - Open SURFH. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006/computer-vision-opensurf.htmlFeature Detection andFeature ExtractionMaximally stable extremal regions (MSER)J. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002http:/www.robots.ox.ac.uk/vgg/research/affine/Feature ExtractionGIST DescriptorA. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope, IJCV, 2001/torralba/code/spatialenvelope/Feature Detection andFeature ExtractionColor DescriptorK. E. A. van de Sande, T. Gevers and Cees G. M. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, PAMI, 2010http:/koen.me/research/colordescriptors/Feature ExtractionLocal Self-Similarity DescriptorE. Shechtman and M. Irani. Matching local self-similarities across images and videos, CVPR, 2007http:/www.robots.ox.ac.uk/vgg/software/SelfSimilarity/Feature Detection andFeature ExtractionMaximally stable extremal regions (MSER) - VLFeatJ. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002/Feature ExtractionPyramids of Histograms of Oriented Gradients (PHOG)A. Bosch, A. Zisserman, and X. Munoz, Representing shape with a spatial pyramid kernel, CIVR, 2007http:/www.robots.ox.ac.uk/vgg/research/caltech/phog/phog.zipFeature Detection andFeature ExtractionAffine Covariant FeaturesT. Tuytelaars and K. Mikolajczyk, Local Invariant Feature Detectors: A Survey, Foundations and Trends in Computer Graphics and Vision, 2008http:/www.robots.ox.ac.uk/vgg/research/affine/Feature ExtractionsRD-SIFTM. Lourenco, J. P. Barreto and A. Malti, Feature Detection and Matching in Images with Radial Distortion, ICRA 2010http:/arthronav.isr.uc.pt/mlourenco/srdsift/index.html#Graph MatchingReweighted Random Walks for Graph MatchingM. Cho, J. Lee, and K. M. Lee, Reweighted Random Walks for Graph Matching, ECCV 2010http:/cv.snu.ac.kr/research/RRWM/Graph MatchingHyper-graph Matching via Reweighted Random WalksJ. Lee, M. Cho, K. M. Lee. Hyper-graph Matching via Reweighted Random Walks, CVPR 2011http:/cv.snu.ac.kr/research/RRWHM/Illumination, Reflectance, and ShadowWebcam Clip Art: Appearance and Illuminant Transfer from Time-lapse SequencesJ-F. Lalonde, A. A. Efros, S. G. Narasimhan, Webcam Clip Art: Appearance and Illuminant Transfer from Time-lapse Sequences, SIGGRAPH Asia 2009/jlalonde/software.html#skyModelIllumination, Reflectance, and ShadowGround shadow detectionJ.-F. Lalonde, A. A. Efros, S. G. Narasimhan, Detecting Ground Shadowsin Outdoor Consumer Photographs, ECCV 2010/software.html#shadowDetectionIllumination, Reflectance, and ShadowShadow Detection using Paired RegionR. Guo, Q. Dai and D. Hoiem, Single-Image Shadow Detection and Removal using Paired Regions, CVPR 2011/homes/guo29/projects/shadow.htmlIllumination, Reflectance, and ShadowReal-time Specular Highlight RemovalQ. Yang, S. Wang and N. Ahuja, Real-time Specular Highlight Removal Using Bilateral Filtering, ECCV 2010.hk/qiyang/publications/code/eccv-10.zipIllumination, Reflectance, and ShadowEstimating Natural Illumination from a Single Outdoor ImageJ-F. Lalonde, A. A. Efros, S. G. Narasimhan, Estimating Natural Illumination from a Single Outdoor Image , ICCV 2009/jlalonde/software.html#skyModelIllumination, Reflectance, and ShadowWhat Does the Sky Tell Us About the Camera?J-F. Lalonde, S. G. Narasimhan, A. A. Efros, What Does the Sky Tell Us About the Camera?, ECCV 2008/jlalonde/software.html#skyModelImage ClassificationLocality-constrained Linear CodingJ. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained Linear Coding for Image Classification, CVPR, 2010/jyang29/LLC.htmImage ClassificationSparse Coding for Image ClassificationJ. Yang, K. Yu, Y. Gong, T. Huang, Linear Spatial Pyramid Matching using Sparse Coding for Image Classification, CVPR, 2009/jyang29/ScSPM.htmImage ClassificationTexture ClassificationM. Varma and A. Zisserman, A statistical approach to texture classification from single images, IJCV2005http:/www.robots.ox.ac.uk/vgg/research/texclass/index.htmlFeature Matching andImage ClassificationThe Pyramid Match: Efficient Matching for Retrieval and RecognitionK. Grauman and T. Darrell. The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, ICCV 2005/grauman/research/projects/pmk/pmk_projectpage.htmImage ClassificationSpatial Pyramid MatchingS. Lazebnik, C. Schmid, and J. Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, CVPR 2006/lazebnik/research/SpatialPyramid.zipImage DeblurringRadon TransformT. S. Cho, S. Paris, B. K. P. Horn, W. T. Freeman, Blur kernel estimation using the radon transform, CVPR 2011/taegsang/Documents/RadonDeblurringCode.zipImage DeblurringAnalyzing spatially varying blurA. Chakrabarti, T. Zickler, and W. T. Freeman, Analyzing Spatially-varying Blur, CVPR 2010/ayanc/svblur/Image Denoising,Image Super-resolution, and Image DeblurringLearning Models of Natural Image PatchesD. Zoran and Y. Weiss, From Learning Models of Natural Image Patches to Whole Image Restoration, ICCV, 2011http:/www.cs.huji.ac.il/daniez/Image DeblurringNon-blind deblurring (and blind denoising) with integrated noise estimationU. Schmidt, K. Schelten, and S. Roth. Bayesian deblurring with integrated noise estimation, CVPR 2011http:/www.gris.tu-darmstadt.de/research/visinf/software/index.en.htmImage DeblurringEficient Marginal Likelihood Optimization in Blind DeconvolutionA. Levin, Y. Weiss, F. Durand, W. T. Freeman. Efficient Marginal Likelihood Optimization in Blind Deconvolution, CVPR 2011http:/www.wisdom.weizmann.ac.il/levina/papers/LevinEtalCVPR2011Code.zipImage DeblurringRichardson-Lucy Deblurring for Scenes under Projective Motion PathY.-W. Tai, P. Tan, M. S. Brown: Richardson-Lucy Deblurring for Scenes under Projective Motion Path, PAMI 2011http:/yuwing.kaist.ac.kr/projects/projectivedeblur/projectivedeblur_files/ProjectiveDeblur.zipImage DenoisingSparsity-based Image DenoisingW. Dong, X. Li, L. Zhang and G. Shi, Sparsity-based Image Denoising vis Dictionary Learning and Structural Clustering, CVPR, 2011/xinl/CSR.htmlImage DenoisingK-SVDhttp:/www.cs.technion.ac.il/ronrubin/Software/ksvdbox13.zipImage DenoisingClustering-based DenoisingP. Chatterjee and P. Milanfar, Clustering-based Denoising with Locally Learned Dictionaries (K-LLD), TIP, 2009/priyam/K-LLD/Image DenoisingBLS-GSMhttp:/decsai.ugr.es/javier/denoise/Image DenoisingField of Experts/roth/research/software.htmlImage DenoisingNon-local Meanshttp:/dmi.uib.es/abuades/codis/NLmeansfilter.mImage DenoisingWhat makes a good model of natural images ?Y. Weiss and W. T. Freeman, CVPR 2007http:/www.cs.huji.ac.il/yweiss/BRFOE.zipImage DenoisingBM3Dhttp:/www.cs.tut.fi/foi/GCF-BM3D/Image DenoisingKernel Regressions/htakeda/MatlabApp/KernelRegressionBasedImageProcessingToolBox_ver1-1beta.zipImage DenoisingGaussian Field of Expertshttp:/www.cs.huji.ac.il/yweiss/BRFOE.zipImage DenoisingNonlocal means with cluster treesT. Brox, O. Kleinschmidt, D. Cremers, Efficient nonlocal means for denoising of textural patterns, TIP 2008rmatik.uni-freiburg.de/resources/binaries/nlmeans_brox_tip08Linux64.zipImage FilteringGradientShopP. Bhat, C.L. Zitnick, M. Cohen, B. Curless, and J. Kim, GradientShop: A Gradient-Domain Optimization Framework for Image and Video Filtering, TOG 2010/projects/gradientshop/Image FilteringWeighted Least Squares FilterZ. Farbman, R. Fattal, D. Lischinski, R. Szeliski, Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation, SIGGRAPH 2008http:/www.cs.huji.ac.il/danix/epd/Image FilteringReal-time O(1) Bilateral FilteringQ. Yang, K.-H. Tan and N. Ahuja, Real-time O(1) Bilateral Filtering, CVPR 2009/qyang6/publications/code/qx_constant_time_bilateral_filter_ss.zipImage FilteringGuided Image FilteringK. He, J. Sun, X. Tang, Guided Image Filtering, ECCV 2010.hk/hkm007/eccv10/guided-filter-code-v1.rarImage FilteringFast Bilateral FilterS. Paris and F. Durand, A Fast Approximation of the Bilateral Filter using a Signal Processing Approach, ECCV, 2006/sparis/bf/Image FilteringImage smoothing via L0 Gradient MinimizationL. Xu, C. Lu, Y. Xu, J. Jia, Image smoothing via L0 Gradient Minimization, SIGGRAPH Asia 2011.hk/leojia/projects/L0smoothing/L0smoothing.zipImage FilteringDomain TransformationE. Gastal, M. Oliveira, Domain Transform for Edge-Aware Image and Video Processing, SIGGRAPH 2011http:/inf.ufrgs.br/eslgastal/DomainTransform/DomainTransformFilters-Source-v1.0.zipImage Processing andImage FilteringPiotrs Image & Video Matlab ToolboxPiotr Dollar, Piotrs Image & Video Matlab Toolbox, /pdollar/toolbox/doc/index.html/pdollar/toolbox/doc/index.htmlImage FilteringLocal Laplacian FiltersS. Paris, S. Hasinoff, J. Kautz, Local Laplacian Filters: Edge-Aware Image Processing with a Laplacian Pyramid, SIGGRAPH 2011/sparis/publi/2011/siggraph/matlab_source_code.zipImage FilteringSVM for Edge-Preserving Fil