This paper presents a method for monitoring activities at a ticket vending machine in a video-surveillance context. Rather than relying on the output of a tracking module, which is prone to errors, the events are direclty recognized from image measurements. This especially does not require tracking. A statistical layered approach is proposed, where in the first layer, several sub-events are defined and detected using a discriminative approach. The second layer uses the result of the first and models the temporal relationships of the high-level event using a Hidden Markov Model (HMM). Results are assessed on 3h30 hours of real video footage coming from Turin metro station.
Alexandre Massoud Alahi, Mohamed Ossama Ahmed Abdelfattah, Mariam Ahmed Mahmoud Hegazy Hassan
Victor Panaretos, Laya Ghodrati
Mathieu Salzmann, Jiancheng Yang, Zheng Dang, Zhen Wei, Haobo Jiang