Hands off : a handshake interaction detection and localization model for COVID-19 threat control
Date
2021-10-18
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Abstract
A handshake interaction localization model in real-time that may help mitigate the threat for transmitting COVID-19, is presented using computer vision in a non-intrusive technique. A real-time detection model (using YOLO/you only look once) is proposed to identify handshake interactions in realistic scenarios. YOLO can detect multiple interactions in a single frame. The model can be applied to public spaces to identify handshake interactions. The study is the first to use a human interaction localization model in a multi-person setting. YOLO is a convolutional neural network (CNN) for object detection in real-time.
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Conference Paper
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Keywords
LOCALIZATION, MATHEMATICAL MODELS, COVID-19, ARTIFICIAL INTELLIGENCE, HUMAN RIGHTS, DISEASE TRANSMISSION, EPIDEMIOLOGY, SOCIAL BEHAVIOUR, SIMULATION, SRI LANKA, SOUTH ASIA