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 non-intrusive 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.