Real-Time Face Tracking for Context-Aware Computing

The use of context can be a very relevant cue for computer vision based systems in order to eliminate a lot of ambiguity and uncertainty otherwise inherent in the human computer interaction Despite of the fact that its obvious importance is widely acknowledged the great majority of the systems nowdays still lack of this capability In this paper we propose faces as a primary contextual in formation for person detection and present face tracking as a basic procedure for context driven focus of attention applications Our proposal was implemented in a combined system by integrating a motion based approach (Particle Filter) and a model based approach (Ada Boost)