Trade-off between accuracy and speed for pedestrian detection using HOG feature

In order to detect pedestrians in many applications, histogram of oriented gradient (HOG) feature is widely used. Although HOG feature can provide high detection accuracy, fast detection time is hardly achieved due to its computational complexity. In this paper, a new method for pedestrian detection using HOG feature is proposed to achieve both high detection rate and fast detection time. Multi-scale cells and blocks of HOG feature are used to improve detection accuracy, and they are computed by using integral HOG to improve detection speed. In order to further improve detection quality in terms of accuracy and speed, two-stage approach is adopted in the proposed method. Experimental results show that the proposed method improves both detection rate and speed.