An overview of methods for control and estimation of capacity in COVID-19 pandemic from point cloud and imagery data

Abstract

The main actions to control the COVID-19 pandemic and prevent the spread of the virus have focused on population control and social distancing. Over the years, many applications of sensing technologies have shown their effectiveness in solving problems related to the acquisition, identification and modelling of the environment, although not always from a human-centred approach. This chapter compiles sensing techniques from point cloud and imagery data related to population control and estimation of the capacity: people counting, biometric identification, monitoring of activities, distance measurement and 3D modelling. The current state-of-the-art techniques and the most common algorithms are summarized. Finally, the advantages and disadvantages of point cloud data and imagery are discussed, as well as the current trends of the predominant technology in each field.