Zhihan Liu1, Xiang Li1, Siqi Liu2, Wei Li1,*, Xiangxu Meng1, Jing Jia3
Computer Systems Science and Engineering, Vol.47, No.1, pp. 937-954, 2023, DOI:10.32604/csse.2023.039417
Abstract The COVID-19 virus is usually spread by small droplets when talking, coughing and sneezing, so maintaining physical distance between people is necessary to slow the spread of the virus. The World Health Organization (WHO) recommends maintaining a social distance of at least six feet. In this paper, we developed a real-time pedestrian social distance risk alert system for COVID-19, which monitors the distance between people in real-time via video streaming and provides risk alerts to the person in charge, thus avoiding the problem of too close social distance between pedestrians in public places. We design a lightweight convolutional neural network… More >