Online Multiperson Tracking and Counting with Cloud Computing
Weishan Zhang, Wenshan Wang, Pengcheng Duan, Xin Liu, Qinghua Lu · 2014
Intelligent video surveillance is a challenging issue due to complicated scenes. Based on empirical and experimental explorations, we propose a multi-person tracking-by-detection framework to achieve pedestrian counting at run time. This framework is integrated with a stream based cloud computing paradigm to improve tracking performance. We evaluated our approach which shows improved time performance compared with those classical approaches.