机器视觉开源代码集合.docx
- 文档编号:29116683
- 上传时间:2023-07-20
- 格式:DOCX
- 页数:20
- 大小:23.83KB
机器视觉开源代码集合.docx
《机器视觉开源代码集合.docx》由会员分享,可在线阅读,更多相关《机器视觉开源代码集合.docx(20页珍藏版)》请在冰豆网上搜索。
机器视觉开源代码集合
机器视觉开源代码集合
一、特征提取FeatureExtraction:
∙SIFT[1][Demoprogram][SIFTLibrary][VLFeat]
∙PCA-SIFT[2][Project]
∙Affine-SIFT[3][Project]
∙SURF[4][OpenSURF][MatlabWrapper]
∙AffineCovariantFeatures[5][Oxfordproject]
∙MSER[6][Oxfordproject][VLFeat]
∙GeometricBlur[7][Code]
∙LocalSelf-SimilarityDescriptor[8][Oxfordimplementation]
∙GlobalandEfficientSelf-Similarity[9][Code]
∙HistogramofOrientedGraidents[10][INRIAObjectLocalizationToolkit][OLTtoolkitforWindows]
∙GIST[11][Project]
∙ShapeContext[12][Project]
∙ColorDescriptor[13][Project]
∙PyramidsofHistogramsofOrientedGradients[Code]
∙Space-TimeInterestPoints(STIP)[14][Project][Code]
∙BoundaryPreservingDenseLocalRegions[15][Project]
∙WeightedHistogram[Code]
∙Histogram-basedInterestPointsDetectors[Paper][Code]
∙AnOpenCV-C++implementationofLocalSelfSimilarityDescriptors[Project]
∙FastSparseRepresentationwithPrototypes[Project]
∙CornerDetection[Project]
∙AGASTCornerDetector:
fasterthanFASTandevenFAST-ER[Project]
∙Real-timeFacialFeatureDetectionusingConditionalRegressionForests[Project]
∙GlobalandEfficientSelf-SimilarityforObjectClassificationandDetection[code]
∙WαSH:
Weightedα-ShapesforLocalFeatureDetection[Project]
∙HOG[Project]
∙OnlineSelectionofDiscriminativeTrackingFeatures[Project]
二、图像分割ImageSegmentation:
∙NormalizedCut[1][Matlabcode]
∙GergMori’Superpixelcode[2][Matlabcode]
∙EfficientGraph-basedImageSegmentation[3][C++code][Matlabwrapper]
∙Mean-ShiftImageSegmentation[4][EDISONC++code][Matlabwrapper]
∙OWT-UCMHierarchicalSegmentation[5][Resources]
∙Turbepixels[6][Matlabcode32bit][Matlabcode64bit][Updatedcode]
∙Quick-Shift[7][VLFeat]
∙SLICSuperpixels[8][Project]
∙SegmentationbyMinimumCodeLength[9][Project]
∙BiasedNormalizedCut[10][Project]
∙SegmentationTree[11-12][Project]
∙EntropyRateSuperpixelSegmentation[13][Code]
∙FastApproximateEnergyMinimizationviaGraphCuts[Paper][Code]
∙EfficientPlanarGraphCutswithApplicationsinComputerVision[Paper][Code]
∙IsoperimetricGraphPartitioningforImageSegmentation[Paper][Code]
∙RandomWalksforImageSegmentation[Paper][Code]
∙BlossomV:
Anewimplementationofaminimumcostperfectmatchingalgorithm[Code]
∙AnExperimentalComparisonofMin-Cut/Max-FlowAlgorithmsforEnergyMinimizationinComputerVision[Paper][Code]
∙GeodesicStarConvexityforInteractiveImageSegmentation[Project]
∙ContourDetectionandImageSegmentationResources[Project][Code]
∙BiasedNormalizedCuts[Project]
∙Max-flow/min-cut[Project]
∙Chan-VeseSegmentationusingLevelSet[Project]
∙AToolboxofLevelSetMethods[Project]
∙Re-initializationFreeLevelSetEvolutionviaReactionDiffusion[Project]
∙ImprovedC-Vactivecontourmodel[Paper][Code]
∙AVariationalMultiphaseLevelSetApproachtoSimultaneousSegmentationandBiasCorrection[Paper][Code]
∙LevelSetMethodResearchbyChunmingLi[Project]
∙ClassCutforUnsupervisedClassSegmentation[code]
∙SEEDS:
SuperpixelsExtractedviaEnergy-DrivenSampling [Project][other]
三、目标检测ObjectDetection:
∙Asimpleobjectdetectorwithboosting[Project]
∙INRIAObjectDetectionandLocalizationToolkit[1][Project]
∙DiscriminativelyTrainedDeformablePartModels[2][Project]
∙CascadeObjectDetectionwithDeformablePartModels[3][Project]
∙Poselet[4][Project]
∙ImplicitShapeModel[5][Project]
∙ViolaandJones’sFaceDetection[6][Project]
∙BayesianModellingofDyanmicScenesforObjectDetection[Paper][Code]
∙Handdetectionusingmultipleproposals[Project]
∙ColorConstancy,IntrinsicImages,andShapeEstimation[Paper][Code]
∙Discriminativelytraineddeformablepartmodels[Project]
∙GradientResponseMapsforReal-TimeDetectionofTexture-LessObjects:
LineMOD[Project]
∙ImageProcessingOnLine[Project]
∙RobustOpticalFlowEstimation[Project]
∙Where'sWaldo:
MatchingPeopleinImagesofCrowds[Project]
∙ScalableMulti-classObjectDetection[Project]
∙Class-SpecificHoughForestsforObjectDetection[Project]
∙DeformedLatticeDetectionInReal-WorldImages[Project]
∙Discriminativelytraineddeformablepartmodels[Project]
四、显著性检测SaliencyDetection:
∙Itti,Koch,andNiebur’saliencydetection[1][Matlabcode]
∙Frequency-tunedsalientregiondetection[2][Project]
∙Saliencydetectionusingmaximumsymmetricsurround[3][Project]
∙AttentionviaInformationMaximization[4][Matlabcode]
∙Context-awaresaliencydetection[5][Matlabcode]
∙Graph-basedvisualsaliency[6][Matlabcode]
∙Saliencydetection:
Aspectralresidualapproach.[7][Matlabcode]
∙Segmentingsalientobjectsfromimagesandvideos.[8][Matlabcode]
∙SaliencyUsingNaturalstatistics.[9][Matlabcode]
∙DiscriminantSaliencyforVisualRecognitionfromClutteredScenes.[10][Code]
∙LearningtoPredictWhereHumansLook[11][Project]
∙GlobalContrastbasedSalientRegionDetection[12][Project]
∙BayesianSaliencyviaLowandMidLevelCues[Project]
∙Top-DownVisualSaliencyviaJointCRFandDictionaryLearning[Paper][Code]
∙SaliencyDetection:
ASpectralResidualApproach[Code]
五、图像分类、聚类ImageClassification,Clustering
∙PyramidMatch[1][Project]
∙SpatialPyramidMatching[2][Code]
∙Locality-constrainedLinearCoding[3][Project][Matlabcode]
∙SparseCoding[4][Project][Matlabcode]
∙TextureClassification[5][Project]
∙MultipleKernelsforImageClassification[6][Project]
∙FeatureCombination[7][Project]
∙SuperParsing[Code]
∙LargeScaleCorrelationClusteringOptimization[Matlabcode]
∙DetectingandSketchingtheCommon[Project]
∙Self-TuningSpectralClustering[Project][Code]
∙UserAssistedSeparationofReflectionsfromaSingleImageUsingaSparsityPrior[Paper][Code]
∙FiltersforTextureClassification[Project]
∙MultipleKernelLearningforImageClassification[Project]
∙SLICSuperpixels[Project]
六、抠图ImageMatting
∙AClosedFormSolutiontoNaturalImageMatting[Code]
∙SpectralMatting[Project]
∙Learning-basedMatting[Code]
七、目标跟踪ObjectTracking:
∙AForestofSensors-TrackingAdaptiveBackgroundMixtureModels[Project]
∙ObjectTrackingviaPartialLeastSquaresAnalysis[Paper][Code]
∙RobustObjectTrackingwithOnlineMultipleInstanceLearning[Paper][Code]
∙OnlineVisualTrackingwithHistogramsandArticulatingBlocks[Project]
∙IncrementalLearningforRobustVisualTracking[Project]
∙Real-timeCompressiveTracking[Project]
∙RobustObjectTrackingviaSparsity-basedCollaborativeModel[Project]
∙VisualTrackingviaAdaptiveStructuralLocalSparseAppearanceModel[Project]
∙OnlineDiscriminativeObjectTrackingwithLocalSparseRepresentation[Paper][Code]
∙SuperpixelTracking[Project]
∙LearningHierarchicalImageRepresentationwithSparsity,SaliencyandLocality[Paper][Code]
∙OnlineMultipleSupportInstanceTracking[Paper][Code]
∙VisualTrackingwithOnlineMultipleInstanceLearning[Project]
∙Objectdetectionandrecognition[Project]
∙CompressiveSensingResources[Project]
∙RobustReal-TimeVisualTrackingusingPixel-WisePosteriors[Project]
∙Tracking-Learning-Detection[Project][OpenTLD/C++Code]
∙theHandVu:
vision-basedhandgestureinterface[Project]
∙LearningProbabilisticNon-LinearLatentVariableModelsforTrackingComplexActivities[Project]
八、Kinect:
∙Kinecttoolbox[Project]
∙OpenNI[Project]
∙zouxy09CSDNBlog[Resource]
∙FingerTracker手指跟踪[code]
九、3D相关:
∙3DReconstructionofaMovingObject[Paper][Code]
∙ShapeFromShadingUsingLinearApproximation[Code]
∙CombiningShapefromShadingandStereoDepthMaps[Project][Code]
∙ShapefromShading:
ASurvey[Paper][Code]
∙ASpatio-TemporalDescriptorbasedon3DGradients(HOG3D)[Project][Code]
∙Multi-cameraSceneReconstructionviaGraphCuts[Paper][Code]
∙AFastMarchingFormulationofPerspectiveShapefromShadingunderFrontalIllumination[Paper][Code]
∙Reconstruction:
3DShape,Illumination,Shading,Reflectance,Texture[Project]
∙MonocularTrackingof3DHumanMotionwithaCoordinatedMixtureofFactorAnalyzers[Code]
∙Learning3-DSceneStructurefromaSingleStillImage[Project]
十、机器学习算法:
∙MatlabclassforcomputingApproximateNearestNieghbor(ANN)[Matlabclass providinginterfacetoANNlibrary]
∙RandomSampling[code]
∙ProbabilisticLatentSemanticAnalysis(pLSA)[Code]
∙FASTANNandFASTCLUSTERforapproximatek-means(AKM)[Project]
∙FastIntersection/AdditiveKernelSVMs[Project]
∙SVM[Code]
∙Ensemblelearning[Project]
∙DeepLearning[Net]
∙DeepLearningMethodsforVision[Project]
∙NeuralNetworkforRecognitionofHandwrittenDigits[Project]
∙TrainingadeepautoencoderoraclassifieronMNISTdigits[Project]
∙THEMNISTDATABASEofhandwrittendigits[Project]
∙Ersatz:
deepneuralnetworksinthecloud[Project]
∙DeepLearning[Project]
∙sparseLM:
SparseLevenberg-MarquardtnonlinearleastsquaresinC/C++[Project]
∙Weka3:
DataMiningSoftwareinJava[Project]
∙Invitedtalk"ATutorialonDeepLearning"byDr.KaiYu(余凯)[Video]
∙CNN-Convolutionalneuralnetworkclass[MatlabTool]
∙YannLeCun'sPublications[Wedsite]
∙LeNet-5,convolutionalneuralnetworks[Project]
∙TrainingadeepautoencoderoraclassifieronMNISTdigits[Project]
∙DeepLearning大牛GeoffreyE.Hinton'sHomePage[Website]
∙MultipleInstanceLogisticDiscriminant-basedMetricLearning(MildML)andLogisticDiscriminant-basedMetricLearning(LDML)[Code]
∙Sparsecodingsimulationsoftware[Project]
∙VisualRecognitionandMachineLearningSummerSchool[Software]
十一、目标、行为识别Object,ActionRecognition:
∙ActionRecognitionbyDenseTrajectories[Project][Code]
∙ActionRecognitionUsingaDistri
- 配套讲稿:
如PPT文件的首页显示word图标,表示该PPT已包含配套word讲稿。双击word图标可打开word文档。
- 特殊限制:
部分文档作品中含有的国旗、国徽等图片,仅作为作品整体效果示例展示,禁止商用。设计者仅对作品中独创性部分享有著作权。
- 关 键 词:
- 机器 视觉 源代码 集合