Video-based social distancing evaluation in the cosmos testbed pilot site

Abstract

Social distancing can reduce infection rates in respiratory pandemics such as COVID-19, especially in dense urban areas. Hence, we used the PAWR COSMOS wireless edge-cloud testbed in New York City to design and evaluate two different approaches for social distancing analysis. The first, \textbf{Auto}mated video-based \textbf{S}ocial \textbf{D}istancing \textbf{A}nalyzer (\textbf{Auto-SDA}), was designed to measure pedestrians compliance with social distancing protocols using street-level cameras. However, since using street-level cameras can raise privacy concerns, we also developed the \textbf{B}ird's eye view \textbf{S}ocial \textbf{D}istancing \textbf{A}nalyzer (\textbf{B-SDA}) which uses bird's eye view cameras, thereby preserving pedestrians' privacy. Both Auto-SDA and B-SDA consist of multiple modules. This demonstration illustrates the roles of these modules and their overall performance in evaluating the compliance of pedestrians with social distancing protocols. Moreover, we demonstrate applying Auto-SDA and B-SDA on videos recorded from cameras deployed on the 2nd and 12th floor of Columbia's Mudd building, respectively.