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Authors: Gona Rozhbayani 1 ; Amel Tuama 1 and Fadwa Al-Azzo 2

Affiliations: 1 Kirkuk Technical Engineering College, Northern Technical University, Kirkuk 36001, Iraq ; 2 Technical Engineering College Mosul, Northern Technical University, Mosul 41001, Iraq

Keyword(s): Human Detection, Social Distancing, Deep Learning, YOLOv5.

Abstract: The objective of this study is to offer a YOLOv5 deep learning-based system for social distance monitoring. The YOLOv5 model has been used to detect humans in real- time video frames, and to obtain information on the detected bounding box for the bird’s eye view perspective technique. The pairwise distances of the identified bounding box centroid of people are calculated by utilizing euclidean distance. In addition, a threshold value has been set and applied as an approximation of social distance to pixels for determining social distance violations between people. The effectiveness of this proposed system is tested by experiments on different four video frames. The suggested system’s performance showed a high level of efficiency in monitoring social distancing accurately up to 100%.

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Paper citation in several formats:
Rozhbayani, G.; Tuama, A. and Al-Azzo, F. (2024). Social Distancing Monitoring by Human Detection Through Bird’s-Eye View Technique. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 306-313. DOI: 10.5220/0012373900003660

@conference{visapp24,
author={Gona Rozhbayani. and Amel Tuama. and Fadwa Al{-}Azzo.},
title={Social Distancing Monitoring by Human Detection Through Bird’s-Eye View Technique},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={306-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012373900003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Social Distancing Monitoring by Human Detection Through Bird’s-Eye View Technique
SN - 978-989-758-679-8
IS - 2184-4321
AU - Rozhbayani, G.
AU - Tuama, A.
AU - Al-Azzo, F.
PY - 2024
SP - 306
EP - 313
DO - 10.5220/0012373900003660
PB - SciTePress

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