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arXiv · 2105.10935

Principled information fusion for multi-view multi-agent surveillance systems

Bailu Wang·Suqi Li·Giorgio Battistelli·Luigi Chisci·Wei Yi
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Abstract

A key objective of multi-agent surveillance systems is to monitor a much larger region than the limited field-of-view (FoV) of any individual agent by successfully exploiting cooperation among multi-view agents. Whenever either a centralized or a distributed approach is pursued, this goal cannot be achieved unless an appropriately designed fusion strategy is adopted. This paper presents a novel principled information fusion approach for dealing with multi-view multi-agent case, on the basis of Generalized Covariance Intersection (GCI). The proposed method can be used to perform multi-object tracking on both a centralized and a distributed peer-to-peer sensor network. Simulation experiments on realistic multi-object tracking scenarios demonstrate effectiveness of the proposed solution.

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Bailu Wang, Suqi Li, Giorgio Battistelli, Luigi Chisci, Wei Yi. 2021-05-23. Principled information fusion for multi-view multi-agent surveillance systems. https://arxiv.org/abs/2105.10935

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