Journal
2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
Volume -, Issue -, Pages -Publisher
IEEE
DOI: 10.1109/IJCNN52387.2021.9534231
Keywords
social distancing; deep learning; object detection; artificial intelligence; Coronavirus; COVID-19
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Funding
- MIUR - Secure-OpenNets
- EU SPARTA [830892]
- CyberSANE projects
- EU project CyberSure [734815]
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Social distancing has become crucial in controlling the spread of infectious diseases like COVID-19. A social distancing detector has been proposed to monitor violations and ensure compliance, with potential for further improvement.
Social distancing is becoming really important in last month as a vehicle to limit the COVID-19 Coronavirus pandemic. Generally speaking, it is effective to control the spread of contagious diseases. In this context there is the need to monitor social distancing violations: for this reason in this paper we propose a social distancing detector able to count the violations by analysing video streams. Preliminary results show that the proposed method can be employed to guarantee social distancing. Moreover we discuss several suggestions aimed to improve the following proposal.
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