| Autor: |
Nyan Bo Bo, Francis Deboeverie, Mohamed Eldib, Junzhi Guan, Xingzhe Xie, Jorge Niño, Dirk Van Haerenborgh, Maarten Slembrouck, Samuel Van de Velde, Heidi Steendam, Peter Veelaert, Richard Kleihorst, Hamid Aghajan, Wilfried Philips |
| Jazyk: |
angličtina |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
Sensors, Vol 14, Iss 11, Pp 20800-20824 (2014) |
| Druh dokumentu: |
article |
| ISSN: |
1424-8220 |
| DOI: |
10.3390/s141120800 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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