The 330 Hera features of 3780 dimensions are used as test samples, and the support vector machine (SVM) classifier is used to determine whether the HOG features of these windows are pedestrians and pedestrians are marked with rectangles. HOG pedestrian characteristics and the corresponding SVM classifier parameters, in the opencv has been trained, we only need to get HOG characteristics, and then call SVM to get the results

HOG
HOG\Debug
HOG\Debug\HOG.exe
HOG\Debug\HOG.ilk
HOG\Debug\HOG.pdb
HOG\HOG
HOG\HOG\Debug
HOG\HOG\Debug\HOG.log
HOG\HOG\Debug\HOG.tlog
HOG\HOG\Debug\HOG.tlog\CL.read.1.tlog
HOG\HOG\Debug\HOG.tlog\CL.write.1.tlog
HOG\HOG\Debug\HOG.tlog\HOG.lastbuildstate
HOG\HOG\Debug\HOG.tlog\link.read.1.tlog
HOG\HOG\Debug\HOG.tlog\link.write.1.tlog
HOG\HOG\Debug\hog.obj
HOG\HOG\Debug\hog_detect.obj
HOG\HOG\Debug\vc120.idb
HOG\HOG\Debug\vc120.pdb
HOG\HOG\HOG.vcxproj
HOG\HOG\HOG.vcxproj.filters
HOG\HOG\hog_detect.cpp
HOG\HOG\test.jpg
HOG\HOG\test1.jpg
HOG\HOG.sdf
HOG\HOG.sln
HOG\HOG.v12.suo

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