MetroSurv: Detecting events in subway stations

Video surveillance has become a hot research topic due to the recently increased importance of safety and security issues. Usually, security personnel has to monitor a surveillance area and often they have to do this for 24 h a day. Thus, it would be desirable to develop intelligent surveillance systems that support this task automatically. The system described in this contribution is thought of such an automatic surveillance system that has been developed to detect several dangerous situations in subway stations. The workflow and the most important steps from foreground segmentation, shadow detection, tracking and classification to event detection are described, discussed and evaluated in detail. The developed surveillance system yields satisfying results, as dangerous situations that need to be recognized are detected in most cases.