COUNT PASSENGERS BASED ON HAAR-LIKE FEATURE IN ELEVATOR APPLICATION
Present elevator control use button sensors to determine when and where to dispatch an elevator car, which dont use the number of passengers. In this paper, we analyze images from camera to detect how many persons waiting for the elevator or in an elevator. A novel framework is proposed for optimized elevator schedule. Extended Haar-like features and Adaboost are used to train a head-shoulder classifier. Some images are selected from video according to elevator button callings to detect head-shoulder. To reduce false alarms a post process is added after detecting. Experimental results show the proposed method with post process has higher performance than existed methods. The information of passenger number can be send to elevator control system for effective schedule, which can reduce passengers waiting time and elevators unnecessary stop, finally save energy and reduce maintain fee.
Elevator control system Haar-like features Adaboost Post process
HONG LIU YUE-LIANG QIAN QUN LIU JIN-TAO LI
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
1202-1206
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）