Human Mobility Monitoring in Very Low Resolution Visual Sensor Network

Sensors

Nyan Bo Bo¹  Francis Deboeverie¹  Mohamed Eldib¹  Junzhi Guan¹  Xingzhe Xie¹  Jorge Niño¹  Dirk Van Haerenborgh¹  Maarten Slembrouck¹  Samuel Van de Velde²  Heidi Steendam²  Peter Veelaert¹  Richard Kleihorst¹  Hamid Aghajan¹ 

[1] Image Processing and Interpretation, Gent University/iMinds, Gent 9000, Belgium; E-Mails:;Digital Communications, Gent University/iMinds, Gent 9000, Belgium; E-Mails:

关键词: visual sensor network;    low resolution imagery;    distributed processing;    tracking;    mobility analysis;   

DOI  :  10.3390/s141120800

来源: mdpi

【 摘 要 】

This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 × 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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.