T-Park: ambient intelligence for security in public parks
In this paper, we present joint research activities in computer vision and sensor networks for a distributed surveillance of urban parks. Distributed visual surveillance of urban environments is one of the most interesting scenario in Ambient Intelligence; in addition, the automated monitoring of public parks, often crowded by children and adults, is still a very difficult task due to the number of objects of interests. In this context, integrating the power of low cost sensors with the information provided by cameras can lead to a more reliable solution to people tracking in wide areas. Specifically, the deficiencies of one approach can be (at least partially) covered by the advantages of the other. The goal is to perform people tracking in parks (to achieve trackable parks T Parks), both in zones covered by overlapped cameras and also, thanks to sensors, in zones not covered by any camera. In this paper, we propose a new technique for multi-camera people tracking based on a learning phase to automatically calibrate pairs of cameras and to build Areas of Field Views (AoFoVs) in order to establish consistent labelling of people. In addition, sensor networks distributed at the borders of the AoFoV give an estimation of the probability of people overlapping, triggering specific algorithms of face detection or head counting to identify the single person. The research of T Parks is part of a two-year Italian project called LAICA, intended to provide advanced services for citizens and public officers based of Ambient intelligence technologies.