Abstract
Social distancing is one of the suggested solutions by the health authorities to reduce the spreading speed of the COVID-19 in public areas. A six-foot physical distancing has been set by the majority of public governors as a mandatory social regulation. However, it is difficult to monitor whether individuals practice the social distancing regulation or not. State-of-the-art technologies, such as computer visions, artificial intelligence, and big data analytics, can help for automated people detection and tracking in the crowd for indoor and outdoor environments using surveillance cameras. In this chapter, several types of popular object detection and tracking schemes in monitoring social distancing are illustrated with implementations of a cutting-edge human detection model by testing its reliability using a sample video. A real-world case study for social control management system is also introduced with its architecture designs and implementations in the context of the COVID-19 pandemic.