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Fast Pedestrian Detection Based on Integral Edge Map and Part SVM

It is difficult for the vision-based pedestrian detection to process in real-time because it consumes very long time to searching pedestrian candidates. This paper proposes a real-time pedestrian detection algorithm, which provides fast pedestrian candidate generation by using the integral vertical edge map. The proposed algorithm extracts the HoG feature from the pedestrian candidate ROI region, and performs the pedestrian classification via part-based Linear SVM classifiers and part position detector. The proposed scheme provides fast and reliable pedestrian detection through the integral vertical edge map and the vanishing line-based sliding window candidate ROI generation.