In this paper a system is presented able to acquire images from multiple indoor network cameras and extract contextual information about persons detected within the considered environment. Distributed system architecture allows one to process images from several cameras on a network of PCs. Objects tracking and posture classification techniques are used in order to extract contextual information from video. These information are stored in a remote database that is accessed from an higher level application that is able to interact with users' mobile phones for delivering context-based-services. In particular, proposed scene understanding techniques have been used for implementing an automatic terminal silencing service in case of a meeting and a sos-call in case of a falling person.
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|Titolo:||"Multi-camera indoor video processing for context awareness"|
|Data di pubblicazione:||2007|
|Appare nelle tipologie:||04.01 - Contributo in atti di convegno|