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Deep visual social distancing monitoring to combat COVID-19: A comprehensive survey.
Himeur, Yassine; Al-Maadeed, Somaya; Almaadeed, Noor; Abualsaud, Khalid; Mohamed, Amr; Khattab, Tamer; Elharrouss, Omar.
  • Himeur Y; Computer Science and Engineering Department, Qatar University, Qatar.
  • Al-Maadeed S; Computer Science and Engineering Department, Qatar University, Qatar.
  • Almaadeed N; Computer Science and Engineering Department, Qatar University, Qatar.
  • Abualsaud K; Computer Science and Engineering Department, Qatar University, Qatar.
  • Mohamed A; Computer Science and Engineering Department, Qatar University, Qatar.
  • Khattab T; Electrical Engineering Department, Qatar University, Qatar.
  • Elharrouss O; Computer Science and Engineering Department, Qatar University, Qatar.
Sustain Cities Soc ; 85: 104064, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1956334
ABSTRACT
Since the start of the COVID-19 pandemic, social distancing (SD) has played an essential role in controlling and slowing down the spread of the virus in smart cities. To ensure the respect of SD in public areas, visual SD monitoring (VSDM) provides promising opportunities by (i) controlling and analyzing the physical distance between pedestrians in real-time, (ii) detecting SD violations among the crowds, and (iii) tracking and reporting individuals violating SD norms. To the authors' best knowledge, this paper proposes the first comprehensive survey of VSDM frameworks and identifies their challenges and future perspectives. Typically, we review existing contributions by presenting the background of VSDM, describing evaluation metrics, and discussing SD datasets. Then, VSDM techniques are carefully reviewed after dividing them into two main categories hand-crafted feature-based and deep-learning-based methods. A significant focus is paid to convolutional neural networks (CNN)-based methodologies as most of the frameworks have used either one-stage, two-stage, or multi-stage CNN models. A comparative study is also conducted to identify their pros and cons. Thereafter, a critical analysis is performed to highlight the issues and impediments that hold back the expansion of VSDM systems. Finally, future directions attracting significant research and development are derived.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study Language: English Journal: Sustain Cities Soc Year: 2022 Document Type: Article Affiliation country: J.scs.2022.104064

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study Language: English Journal: Sustain Cities Soc Year: 2022 Document Type: Article Affiliation country: J.scs.2022.104064