Human Mobility Monitoring in Very Low Resolution Visual Sensor Network

作     者：Bo, Nyan Bo Deboeverie, Francis Eldib, Mohamed Guan, Junzhi Xie, Xingzhe Nirio, Jorge Van Haerenborgh, Dirk Slembrouck, Maarten Van de Velde, Samuel Steendam, Heidi Veelaert, Peter Kleihorst, Richard Aghajan, Hamid Philips, Wilfried 

作者机构：Gent Univ IMinds B-9000 Ghent Belgium Ambient Intelligence Res Lab Stanford CA 94305 USA 

出 版 物：《SENSORS》 (传感器)

年 卷 期：2014年第14卷第11期

页      面：20800-20824页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基　　金：agency for Innovation by Science and Technology (IWT) Belgian National Fund for Scientific Research (FWO Flanders) iMinds 

主　　题：visual sensor network low resolution imagery distributed processing tracking mobility analysis 

摘      要：This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 x 30 pixels). The use of very low resolution sensors reduces privacy concern, cost, computation requirement and power consumption. The core of our proposed system is a robust people tracker that uses low resolution videos provided by the visual sensor network. The distributed processing architecture of our tracking system allows all image processing tasks to be done on the digital signal controller in each visual sensor. In this paper, we experimentally show that reliable tracking of people is possible using very low resolution imagery. We also compare the performance of our tracker against a state-of-the-art tracking method and show that our method outperforms. Moreover, the mobility statistics of tracks such as total distance traveled and average speed derived from trajectories are compared with those derived from ground truth given by Ultra-Wide Band sensors. The results of this comparison show that the trajectories from our system are accurate enough to obtain useful mobility statistics.