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• W2890585985 abstract "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." @default.
• W2890585985 created "2018-09-27" @default.
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• W2890585985 date "2018-07-01" @default.
• W2890585985 modified "2023-10-13" @default.
• W2890585985 title "Multi-Sensor Multi-Object Tracking with Different Fields-of-View Using the LMB Filter" @default.
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• W2890585985 doi "https://doi.org/10.23919/icif.2018.8455250" @default.
• W2890585985 hasPublicationYear "2018" @default.
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