A multi‐camera vision system for fall detection and alarm generation

In‐house video surveillance can represent an excellent support for people with some difficulties (e.g. elderly or disabled people) living alone and with a limited autonomy. New hardware technologies and in particular digital cameras are now affordable and they have recently gained credit as tools for (semi‐)automatically assuring people's safety. In this paper a multi‐camera vision system for detecting and tracking people and recognizing dangerous behaviours and events such as a fall is presented. In such a situation a suitable alarm can be sent, e.g. by means of an SMS. A novel technique of warping people's silhouette is proposed to exchange visual information between partially overlapped cameras whenever a camera handover occurs. Finally, a multi‐client and multi‐threaded transcoding video server delivers live video streams to operators/remote users in order to check the validity of a received alarm. Semantic and event‐based transcoding algorithms are used to optimize the bandwidth usage. A two‐room setup has been created in our laboratory to test the performance of the overall system and some of the results obtained are reported.