Abstract: Driving safety research is always one of the hot topics in social life, this paper designs and realizes a real-time pedestrian warning system based on aggregate channel features. The system includes pedestrian detection module, regional division module, monocular vision distance measurement module and warning module. The pedestrian detection module uses the method of combing aggregate channel features with cascade Adaboost classifier to construct channel pyramids, as wellas to quickly detect the pedestrian in video and obtain the key information and motion properties. The monocular vision distance measurement module estimates the distance between pedestrian and vehicle. The warning module judges the degree of danger based on the motion information and presents the response type. This paper made experiments with the record videos in urban environment, and it validated the real-time capability and accuracy of the system.


Key words:  aggregated channel features (ACF), warning system, pedestrian detection, region division, monocular vision distance measurement