Self-Coordinated Target Assignment and Camera Handoff in Distributed Network of Embedded Smart Cameras

Tracking several objects across multiple cameras is essential for collaborative monitoring in distributed camera networks. The tractability of the related optimization aiming at tracking a maximal number of important targets, decreases with the growing number of objects moving across cameras. To tackle this issue, a viable model and sound object representation, which can leverage the power of existing tool at run-time for a fast computation of solution, is required. In this paper, we provide a formalism to object tracking across multiple cameras. A first assignment of objects to cameras is performed at start-up to initialize a set of distributed trackers in embedded cameras. We model the run-time self-coordination problem with target handover by encoding the problem as a run-time binding of objects to cameras. This approach has successively been used in high-level system synthesis. Our model of distributed tracking is based on Answer Set Programming, a declarative programming paradigm, that helps formulate the distribution and target handover problem as a search problem, such that by using existing answer set solvers, we produce stable solutions in real-time by incrementally solving time-based encoded ASP problems. The effectiveness of the proposed approach is proven on a 3-node camera network deployment.

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