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Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations

التفاصيل البيبلوغرافية
العنوان: Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations
المؤلفون: Gihan Jayatilaka, Jameel Hassan, Suren Sritharan, Janith Bandara Senanayaka, Harshana Weligampola, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Janaka Ekanayake, Samath Dharmaratne
المصدر: Applied Sciences, Vol 12, Iss 17, p 8428 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: COVID-19, computer vision, surveillance, artificial intelligence, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Social distancing measures are proposed as the primary strategy to curb the spread of the COVID-19 pandemic. Therefore, identifying situations where these protocols are violated has implications for curtailing the spread of the disease and promoting a sustainable lifestyle. This paper proposes a novel computer vision-based system to analyze CCTV footage to provide a threat level assessment of COVID-19 spread. The system strives to holistically interpret the information in CCTV footage spanning multiple frames to recognize instances of various violations of social distancing protocols, across time and space, as well as identification of group behaviors. This functionality is achieved primarily by utilizing a temporal graph-based structure to represent the information of the CCTV footage and a strategy to holistically interpret the graph and quantify the threat level of the given scene. The individual components are evaluated in a range of scenarios, and the complete system is tested against human expert opinion. The results reflect the dependence of the threat level on people, their physical proximity, interactions, protective clothing, and group dynamics, with a system performance of 76% accuracy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/12/17/8428; https://doaj.org/toc/2076-3417
DOI: 10.3390/app12178428
URL الوصول: https://doaj.org/article/2ec2d921902744fa95b55c7740cd1163
رقم الأكسشن: edsdoj.2ec2d921902744fa95b55c7740cd1163
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app12178428