AbstractWe investigate the problem of pedestrian detection in still images. Sliding window classifiers, notably using the Histogram-of-Gradient (HOG) features proposed by Dalal and Triggs are the state-of-the-art for this task, and we base our method on this approach. We propose a novel eature extracti on scheme which computes implicit ‘soft egmentations’ of image regions into oreground/background. The method yields tronger object/background edges than grayscale gradient alone, suppresses textural and shading variations,and captures local coherence of object appearance.

Acivs09Code\adaboostDetect.cpp
...........\adaboostDetect.h
...........\colorFeatures.cpp
...........\colorFeatures.h
...........\detectAdaboost.h
...........\headTrack.cpp
...........\headTrack.dsp
...........\headTrack.dsw
...........\headTrack.ncb
...........\headTrack.opt
...........\headTrack.plg
...........\particleFilter.cpp
...........\particleFilter.h
...........\Thumbs.db
...........\Tracker.cpp
...........\Tracker.h

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