Description: 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.
File list (Check if you may need any files):
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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