Multi-sensor Multi-object Tracking with Different Fields-of-view Using the LMB Filter
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A key issue in multi-sensor surveillance is the capability to surveil a much larger region than the field-of-view (FoV) of any individual sensor by exploiting cooperation among sensor nodes. Whenever a centralized or distributed information fusion approach is undertaken, this goal cannot be achieved unless a suitable fusion approach is devised. This paper proposes a novel approach for dealing with different FoVs within the context of Generalized Covariance Intersection (GCI) fusion. The approach can be used to perform multi-object tracking on both a centralized and a distributed peer-to-peer sensor network. Simulation experiments on realistic tracking scenarios demonstrate the effectiveness of the proposed solution.
2018 21st International Conference on Information Fusion (FUSION), July 2018, doi: 10.23919/ICIF.2018.8455250