Computer vision application to determine crowdedness in public transport stations
Răzvan Andrei Gheorghiu, Valentin Iordache, Valentin Alexandru Stan · 2021
Computer vision has advanced greatly in the last years, providing a useful tool to extract information from images and video streams, enhancing the capabilities of classical video detection algorithms. In the transport field, it may be used in many applications, like information systems (for people and vehicle count, identification of lost objects, etc.), but is mature enough to be trusted also safety systems (monitoring rails for foreign objects, illegal crossings, and many more). In this article, the authors present a solution to detect crowdedness in public transport stations, that can be helpful for local authorities/public transport operators to make proper decisions regarding anti-Covid measures, but also enhance the response of the public transport system.