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Human mobility monitoring in very low resolution visual sensor network

Bo Bo Nyan (UGent) , Francis Deboeverie (UGent) , Mohamed Eldib, Junzhi Guan (UGent) , Xingzhe Xie (UGent) , Jorge Niño Castañeda (UGent) , Dirk Van Haerenborgh (UGent) , Maarten Slembrouck (UGent) , Samuel Van de Velde, Heidi Steendam (UGent) , et al.
(2014) SENSORS. 14(11). p.20800-20824
Author
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Abstract
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.
Keywords
mobility analysis, tracking, distributed processing, low resolution imagery, visual sensor network

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MLA
Nyan, Bo Bo, et al. “Human Mobility Monitoring in Very Low Resolution Visual Sensor Network.” SENSORS, vol. 14, no. 11, 2014, pp. 20800–24, doi:10.3390/s141120800.
APA
Nyan, B. B., Deboeverie, F., Eldib, M., Guan, J., Xie, X., Niño Castañeda, J., … Philips, W. (2014). Human mobility monitoring in very low resolution visual sensor network. SENSORS, 14(11), 20800–20824. https://doi.org/10.3390/s141120800
Chicago author-date
Nyan, Bo Bo, Francis Deboeverie, Mohamed Eldib, Junzhi Guan, Xingzhe Xie, Jorge Niño Castañeda, Dirk Van Haerenborgh, et al. 2014. “Human Mobility Monitoring in Very Low Resolution Visual Sensor Network.” SENSORS 14 (11): 20800–824. https://doi.org/10.3390/s141120800.
Chicago author-date (all authors)
Nyan, Bo Bo, Francis Deboeverie, Mohamed Eldib, Junzhi Guan, Xingzhe Xie, Jorge Niño Castañeda, Dirk Van Haerenborgh, Maarten Slembrouck, Samuel Van de Velde, Heidi Steendam, Peter Veelaert, Richard Kleihorst, Hamid Aghajan, and Wilfried Philips. 2014. “Human Mobility Monitoring in Very Low Resolution Visual Sensor Network.” SENSORS 14 (11): 20800–20824. doi:10.3390/s141120800.
Vancouver
1.
Nyan BB, Deboeverie F, Eldib M, Guan J, Xie X, Niño Castañeda J, et al. Human mobility monitoring in very low resolution visual sensor network. SENSORS. 2014;14(11):20800–24.
IEEE
[1]
B. B. Nyan et al., “Human mobility monitoring in very low resolution visual sensor network,” SENSORS, vol. 14, no. 11, pp. 20800–20824, 2014.
@article{5749678,
  abstract     = {{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.}},
  author       = {{Nyan, Bo Bo and Deboeverie, Francis and Eldib, Mohamed and Guan, Junzhi and Xie, Xingzhe and Niño Castañeda, Jorge and Van Haerenborgh, Dirk and Slembrouck, Maarten and Van de Velde, Samuel and Steendam, Heidi and Veelaert, Peter and Kleihorst, Richard and Aghajan, Hamid and Philips, Wilfried}},
  issn         = {{1424-8220}},
  journal      = {{SENSORS}},
  keywords     = {{mobility analysis,tracking,distributed processing,low resolution imagery,visual sensor network}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{20800--20824}},
  title        = {{Human mobility monitoring in very low resolution visual sensor network}},
  url          = {{http://doi.org/10.3390/s141120800}},
  volume       = {{14}},
  year         = {{2014}},
}
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