Human Mobility Monitoring in Very Low Resolution Visual Sensor Network

Sensors

卷:14

Heidi Steendam¹  Samuel Van de Velde¹  Peter Veelaert²  Mohamed Eldib²  Xingzhe Xie²  Richard Kleihorst²  Wilfried Philips²  Hamid Aghajan²  Maarten Slembrouck²  Dirk Van Haerenborgh²  Jorge Niño²  Nyan Bo Bo²  Francis Deboeverie²  Junzhi Guan² 

[1] Digital Communications, Gent University/iMinds, Gent 9000, Belgium;

[2] Image Processing and Interpretation, Gent University/iMinds, Gent 9000, Belgium;

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

DOI  :  10.3390/s141120800

来源: DOAJ

【 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】

Unknown