Section: Application Domains

Video Surveillance

The growing feeling of insecurity among the population led private companies as well as public authorities to deploy more and more security systems. For the safety of the public places, the video camera based surveillance techniques are commonly used, but the multiplication of the camera number leads to the saturation of transmission and analysis means (it is difficult to supervise simultaneously hundreds of screens). For example, 1000 cameras are viewed by two security operators for monitoring the subway network of Brussels. In the framework of our works on automatic video interpretation, we have studied the conception of an automatic platform which can assist the video-surveillance operators.

The aim of this platform is to act as a filter, sorting the scenes which can be interesting for a human operator. This platform is based on the cooperation between an image processing component and an interpretation component using artificial intelligent techniques. Thanks to this cooperation, this platform automatically recognize different scenarios of interest in order to alert the operators. These works have been realized with academic and industrial partners, like European projects PASSWORDS, AVS-PV, AVS-RTPW, ADVISOR, AVITRACK CARETAKER, SERKET and CANTATA and more recently, European projects VICoMo and COFRIEND, national projects SIC, VIDEOID, industrial projects RATP, CASSIOPEE, ALSTOM and SNCF. A first set of very simple applications for the indoor night surveillance of supermarket (AUCHAN) showed the feasibility of this approach. A second range of applications has been to investigate the parking monitoring where the rather large viewing angle makes it possible to see many different objects (car, pedestrian, trolley) in a changing environment (illumination, parked cars, trees shacked by the wind, etc.). This set of applications allowed us to test various methods of tracking, trajectory analysis and recognition of typical cases (occlusion, creation and separation of groups, etc.).

We have studied and developed video surveillance techniques in the transport domain which requires the analysis and the recognition of groups of persons observed from lateral and low position viewing angle in subway stations (subways of Nuremberg, Brussels, Charleroi, Barcelona, Rome and Turin). We have worked with industrial companies (Bull, Vigitec, Keeneo) on the conception of a video surveillance intelligent platform which is independent of a particular application. The principal constraints are the use of fixed cameras and the possibility to specify the scenarios to be recognized, which depend on the particular application, based on scenario models which are independent from the recognition system.

In parallel of the video surveillance of subway stations, projects based on the video understanding platform have started for bank agency monitoring, train car surveillance and aircraft activity monitoring to manage complex interactions between different types of objects (vehicles, persons, aircrafts). A new challenge consists in combining video understanding with learning techniques (e.g. data mining) as it is done in the CARETAKER and COFRIEND projects to infer new knowledge on observed scenes.