A motion-based image processing system for detecting potentially dangerous situations in underground railway stations

The timely detection of potentially dangerous situations involving passengers in public transport sites is vital to improve the safety and confidence of the travelling public. Conventional CCTV systems are monitored manually so that a single observer is typically responsible for dealing with tens or hundreds of cameras at a time. Thus, important events might be missed or detected too late for effective action. This paper gives an overview of motion-based methods used in a system developed as part of a EU-funded research project, to detect three important situations of interest to public transport operators. The style has been kept intentionally general so as to provide a good broad understanding of the transport needs being addressed. Emphasis is given to the performance of these methods as assessed with a large set of video recordings supplied by metropolitan railway networks in London, Paris and Milan.