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1.GeometricContext文件是完成图片中几何方向目标分类。
参考文献《Automatic Photo Pop-up》Hoiem 2005
2 GrabCut文件是完成图像中目标交互式分割
参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》
C. Rother 2004
3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码
4 虹膜识别程序是下载的一个通用的虹膜识别程序，可以运行
5 GML_AdaBoost_Matlab_Toolbox是一个很好用的adaboost matlab工具箱
6 libsvm-mat-2.91-1 是用C编写的改进的SVM程序，代码质量很高，提供了matlab接口
7 SIFT_Matlab 是编写的利用sift特征进行的宽基线匹配，代码质量高
8 FLDfisher 是利用fisher 线性降维方法进行人脸识别-1.GeometricContext file is complete the picture in the geometric direction of target classification. References " Automatic Photo Pop-up" Hoiem 2005 2 GrabCut the target file is an interactive segmentation of image reference " " GrabCut " - Interactive Foreground Extraction using Iterated Graph Cuts" C. Rother 2004 3 HOG documents prepared under their own HOG Characteristics of pedestrian detection matlab code 4 iris recognition process is to download a general iris recognition program, you can run 5 GML_AdaBoost_Matlab_Toolbox is a good use of adaboost matlab toolbox 6 libsvm-mat-2.91-1 is written in C to improve the SVM procedures, code of high quality, provides a matlab interface to 7 SIFT_Matlab is prepared for the use of sift features a wide baseline matching, the code is the use of high quality 8 FLDfisher fisher linear dimension reduction method for face recognition
参考文献《Automatic Photo Pop-up》Hoiem 2005
2 GrabCut文件是完成图像中目标交互式分割
参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》
C. Rother 2004
3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码
4 虹膜识别程序是下载的一个通用的虹膜识别程序，可以运行
5 GML_AdaBoost_Matlab_Toolbox是一个很好用的adaboost matlab工具箱
6 libsvm-mat-2.91-1 是用C编写的改进的SVM程序，代码质量很高，提供了matlab接口
7 SIFT_Matlab 是编写的利用sift特征进行的宽基线匹配，代码质量高
8 FLDfisher 是利用fisher 线性降维方法进行人脸识别-1.GeometricContext file is complete the picture in the geometric direction of target classification. References " Automatic Photo Pop-up" Hoiem 2005 2 GrabCut the target file is an interactive segmentation of image reference " " GrabCut " - Interactive Foreground Extraction using Iterated Graph Cuts" C. Rother 2004 3 HOG documents prepared under their own HOG Characteristics of pedestrian detection matlab code 4 iris recognition process is to download a general iris recognition program, you can run 5 GML_AdaBoost_Matlab_Toolbox is a good use of adaboost matlab toolbox 6 libsvm-mat-2.91-1 is written in C to improve the SVM procedures, code of high quality, provides a matlab interface to 7 SIFT_Matlab is prepared for the use of sift features a wide baseline matching, the code is the use of high quality 8 FLDfisher fisher linear dimension reduction method for face recognition
相关搜索： HOG
GrabCut
hog
svm
matlab
虹膜
graph
cuts
hog
MATLAB
iris
recognition
image
segmentation
using
svm
matlab
toolbox
for
image
segmentation
Face
Recognition
using
GRaph
method
GrabCut
hog
svm
matlab
虹膜
graph
cuts
hog
MATLAB
iris
recognition
image
segmentation
using
svm
matlab
toolbox
for
image
segmentation
Face
Recognition
using
GRaph
method
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下载文件列表
上传代码\GeometricContext\LICENSE.txt
........\................\README
........\................\test_dir\results\Thumbs.db
........\................\........\.......\tmpimsp8247727.g.png
........\................\........\.......\tmpimsp8247727.v.png
........\................\........\images\alley01.jpg
........\................\........\......\city10.jpg
........\................\........\......\lakecomo2008.jpg
........\................\........\......\M2U00037[(000047)17-22-11].JPG
........\................\........\......\Thumbs.db
........\................\src\APPgetLabeledImageM2005.asv
........\................\...\APPgetLabeledImageM2005.m
........\................\...\APPtestDirectory.m
........\................\...\APPtestImage.m
........\................\...\APPtestImageM2005.asv
........\................\...\APPtestImageM2005.m
........\................\...\boost_classify.m
........\................\...\classifiers_08_22_2005.mat
........\................\...\Gclassify.mat
........\................\...\ijcvTestImage.m
........\................\...\ijcvTestImageList.m
........\................\...\im2superpixels.m
........\................\...\mccExcludedFiles.log
........\................\...\msLabelMap2Sp.m
........\................\...\photoPopup.m
........\................\...\photoPopupIjcv.m
........\................\...\photoPopupM.m
........\................\...\photoPopupM2005.asv
........\................\...\photoPopupM2005.m
........\................\...\runtrain.asv
........\................\...\runtrain.m
........\................\...\runtrainadaboost.asv
........\................\...\runtrainadaboost.m
........\................\...\segment.exe
........\................\...\segment_directory.pl
........\................\...\vrml\APPcreateGroundPoints.m
........\................\...\....\APPfitGroundHough.m
........\................\...\....\APPlabels2planes.m
........\................\...\....\APPplanes2faces.m
........\................\...\....\APPwriteVrmlModel.m
........\................\...\....\APPwriteVrmlModel.m~
........\................\...\....\APPwriteVrmlModel_v2.m
........\................\...\....\faces2vrml.m
........\................\...\util\calibrateEdgeClassifier.m
........\................\...\....\confidenceImages2pg.m
........\................\...\....\evaluateProbabilityEstimate.m
........\................\...\....\get_used_features.m
........\................\...\....\pg2confidenceImages.m
........\................\...\....\pg2prcurve.m
........\................\...\....\pg2roc.m
........\................\...\....\processSuperpixelImage.m
........\................\...\....\regressMajorityPercentage.m
........\................\...\....\regressMajorityPercentageDT.m
........\................\...\....\segmentation2labels.m
........\................\...\....\segmentation2labels2.m
........\................\...\....\splitpg.m
........\................\...\....\writeAllLabeledImages.m
........\................\...\....\writeConfidenceImages.m
........\................\...\tools\displaySegmentGraph.m
........\................\...\.....\weightedstats\ksdensityw.asv
........\................\...\.....\.............\ksdensityw.m
........\................\...\.....\.............\treefitw.asv
........\................\...\.....\.............\treefitw.m
........\................\...\.....\.............\treetestw.asv
........\................\...\.....\.............\treetestw.m
........\................\...\.....\.............\private\addbisa.m
........\................\...\.....\.............\.......\addinvg.m
........\................\...\.....\.............\.......\addlogi.m
........\................\...\.....\.............\.......\addnaka.m
........\................\...\.....\.............\.......\addrice.m
........\................\...\.....\.............\.......\addtls.m
........\................\...\.....\.............\.......\dfaddbuttons.m
........\................\...\.....\.............\.......\dfaddparamfit.m
........\................\...\.....\.............\.......\dfaddsm
........\................\README
........\................\test_dir\results\Thumbs.db
........\................\........\.......\tmpimsp8247727.g.png
........\................\........\.......\tmpimsp8247727.v.png
........\................\........\images\alley01.jpg
........\................\........\......\city10.jpg
........\................\........\......\lakecomo2008.jpg
........\................\........\......\M2U00037[(000047)17-22-11].JPG
........\................\........\......\Thumbs.db
........\................\src\APPgetLabeledImageM2005.asv
........\................\...\APPgetLabeledImageM2005.m
........\................\...\APPtestDirectory.m
........\................\...\APPtestImage.m
........\................\...\APPtestImageM2005.asv
........\................\...\APPtestImageM2005.m
........\................\...\boost_classify.m
........\................\...\classifiers_08_22_2005.mat
........\................\...\Gclassify.mat
........\................\...\ijcvTestImage.m
........\................\...\ijcvTestImageList.m
........\................\...\im2superpixels.m
........\................\...\mccExcludedFiles.log
........\................\...\msLabelMap2Sp.m
........\................\...\photoPopup.m
........\................\...\photoPopupIjcv.m
........\................\...\photoPopupM.m
........\................\...\photoPopupM2005.asv
........\................\...\photoPopupM2005.m
........\................\...\runtrain.asv
........\................\...\runtrain.m
........\................\...\runtrainadaboost.asv
........\................\...\runtrainadaboost.m
........\................\...\segment.exe
........\................\...\segment_directory.pl
........\................\...\vrml\APPcreateGroundPoints.m
........\................\...\....\APPfitGroundHough.m
........\................\...\....\APPlabels2planes.m
........\................\...\....\APPplanes2faces.m
........\................\...\....\APPwriteVrmlModel.m
........\................\...\....\APPwriteVrmlModel.m~
........\................\...\....\APPwriteVrmlModel_v2.m
........\................\...\....\faces2vrml.m
........\................\...\util\calibrateEdgeClassifier.m
........\................\...\....\confidenceImages2pg.m
........\................\...\....\evaluateProbabilityEstimate.m
........\................\...\....\get_used_features.m
........\................\...\....\pg2confidenceImages.m
........\................\...\....\pg2prcurve.m
........\................\...\....\pg2roc.m
........\................\...\....\processSuperpixelImage.m
........\................\...\....\regressMajorityPercentage.m
........\................\...\....\regressMajorityPercentageDT.m
........\................\...\....\segmentation2labels.m
........\................\...\....\segmentation2labels2.m
........\................\...\....\splitpg.m
........\................\...\....\writeAllLabeledImages.m
........\................\...\....\writeConfidenceImages.m
........\................\...\tools\displaySegmentGraph.m
........\................\...\.....\weightedstats\ksdensityw.asv
........\................\...\.....\.............\ksdensityw.m
........\................\...\.....\.............\treefitw.asv
........\................\...\.....\.............\treefitw.m
........\................\...\.....\.............\treetestw.asv
........\................\...\.....\.............\treetestw.m
........\................\...\.....\.............\private\addbisa.m
........\................\...\.....\.............\.......\addinvg.m
........\................\...\.....\.............\.......\addlogi.m
........\................\...\.....\.............\.......\addnaka.m
........\................\...\.....\.............\.......\addrice.m
........\................\...\.....\.............\.......\addtls.m
........\................\...\.....\.............\.......\dfaddbuttons.m
........\................\...\.....\.............\.......\dfaddparamfit.m
........\................\...\.....\.............\.......\dfaddsm