The detection of congestion in a crowd using discrete moments

The management and control of crowds is crucial to the maintenance of public safety. Since crowd congestion prevents the smooth flow of traffic, possibly creating crammed and potentially unsafe conditions, it is important to closely monitor crowd-congestion conditions, to provide timely data analysis and to evaluate the potential for the development of unsafe conditions. This study proposes a method that uses video-monitoring devices to closely monitor crowd conditions and creates a grid model to efficiently detect crowd congestion and to facilitate the analysis necessary for crowd management.