Smart City Gnosys
Smart city article details
| Title | Bird'S-Eye View Social Distancing Analysis System |
|---|---|
| ID_Doc | 12299 |
| Authors | Yang Z.; Sun M.; Ye H.; Xiong Z.; Zussman G.; Kostic Z. |
| Year | 2022 |
| Published | 2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022 |
| DOI | http://dx.doi.org/10.1109/ICCWorkshops53468.2022.9814627 |
| Abstract | Social distancing can reduce the infection rates in respiratory pandemics such as COVID-19. Traffic intersections are particularly suitable for monitoring and evaluation of social distancing behavior in metropolises. Hence, in this paper, we propose and evaluate a real-time privacy-preserving social distancing analysis system (B-SDA), which uses bird's-eye view video recordings of pedestrians who cross traffic intersections. We devise algorithms for video pre-processing, object detection, and tracking which are rooted in the known computer-vision and deep learning techniques, but modified to address the problem of detecting very small objects/pedestrians captured by a highly elevated camera. We propose a method for incorporating pedestrian grouping for detection of social distancing violations, which achieves 0.92 F1 score. B-SDA is used to compare pedestrian behavior in pre-pandemic and during-pandemic videos in uptown Manhattan, showing that the social distancing violation rate of 15.6% during the pandemic is notably lower than 31.4% prenandemic baseline. © 2022 IEEE. |
| Author Keywords | Object detection; Smart city; Social distancing; Testbeds |
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