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Estimating Interpersonal Distance and Crowd Density with a Single-Edge Camera.
- Source :
- Computers (2073-431X); Nov2021, Vol. 10 Issue 11, p143, 1p
- Publication Year :
- 2021
-
Abstract
- For public safety and physical security, currently more than a billion closed-circuit television (CCTV) cameras are in use around the world. Proliferation of artificial intelligence (AI) and machine/deep learning (M/DL) technologies have gained significant applications including crowd surveillance. The state-of-the-art distance and area estimation algorithms either need multiple cameras or a reference object as a ground truth. It is an open question to obtain an estimation using a single camera without a scale reference. In this paper, we propose a novel solution called E-SEC, which estimates interpersonal distance between a pair of dynamic human objects, area occupied by a dynamic crowd, and density using a single edge camera. The E-SEC framework comprises edge CCTV cameras responsible for capturing a crowd on video frames leveraging a customized YOLOv3 model for human detection. E-SEC contributes an interpersonal distance estimation algorithm vital for monitoring the social distancing of a crowd, and an area estimation algorithm for dynamically determining an area occupied by a crowd with changing size and position. A unified output module generates the crowd size, interpersonal distances, social distancing violations, area, and density per every frame. Experimental results validate the accuracy and efficiency of E-SEC with a range of different video datasets. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2073431X
- Volume :
- 10
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Computers (2073-431X)
- Publication Type :
- Academic Journal
- Accession number :
- 153814925
- Full Text :
- https://doi.org/10.3390/computers10110143