The SmarTrack Project at FBK: Past and Ongoing Efforts on People Tracking for Surveillance and Monitoring

Progress in computer vision research is reshaping the video surveillance sector: high-tech companies are starting to offer CCTV based systems now empowered with Video Analytics, i.e. with software solutions able to generate meaningful alerts by analyzing video feeds. Most surveillance applications target people as their subject of study, where they move, how they behave, and what they carry (or leave unattended); people tracking is therefore becoming a ever more important functionality for new generation technology. In this document we summarize our efforts in realizing SmarTrack, a multi camera people tracker developed by FBK over the last few years. We detail main research results, development efforts and applications, and present current and future research directions

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