Dynamic Resource Allocation for Probabilistic Tracking via Attentive Sensing and Sampling

In the context of Ambient Intelligence a fundamental challenge is the design of monitoring technologies able to infer activities of people at-a-distance, employing nonintrusive sensors. Ideally, such solutions should operate in real time using minimal resources and scale to environments with complex topologies. These requirements naturally emerge in application domains such as Security & Surveillance, Ambient Assisted Living, Retail Monitoring, etc., and new research challenges are to be faced to push current state-of-the-art towards meeting them. In line with this trend, our recent efforts detailed in this paper focus on some of the limitations of traditional multi-camera based tracking methods arising in this context, which are characterized by passive sensing and limited adaptation.