Innovative technologies to estimate public transport load in-real time by video content scene analysis

Abstract Scene Analysis, also said Video Content Analysis, represent today a very important tool in video surveillance sector, because it can control images automatically, doing the same job that people necessarily did up to now. Applications are many and different, in a range that go from security systems to statistic control. The intensive use of Video Analysis in modern CCTV systems has highlighted the need for the products and features to advanced, thus allowing a more precise identification of the event analysis, aimed at substantial reduction of false positive alarms, and then improper. Practical examples concern the perimetral control, with identification of the presence of people and bypassing of border barriers, the identification of unattended luggage left in a specific area, sensing actions graffiti and panic situations. Typical applications in the railway environment can affect the identification of people in the act of crossing the tracks, the detection of standstill in the station, the cross the yellow line. The paper describes Innovative technologies to estimate public transport load in-real time by video content scene analysis. The application is linked to i-tour Project, and is relative to WP2 “Provision of Relevant Data and Data Fitting”. In the detail the application is related to Task T.2.2 – “Provision of innovative collection techniques for detection of public transport load”. This application could be represent an innovative solution concerning the use of Video Analysis systems, because today there aren’t similar systems. Being experiment, haven’t statistic data that regards operations of this kind of system, but is possible to affirm that quality of video analysis, and his accuracy, strictly depend by the quality of framing.