Abstract
Data coming from cameras deployed along an harbour coastline are fused to extract the state of unknown vessels framed by the sensors. We embed the ship dynamic model into a Factor Graph that through probability propagation provides a very flexible merge of sensory data and inferences. Preliminary results and experiments from videos gathered in the Gulf of Naples are reported with a discussion on future trends.
This work has been partially sponsored by Ministero Infrastrutture e Trasporti, PON01-01936, Harbour Traffic Optimization System (HABITAT) with Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT)- Italy.
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© 2014 Springer International Publishing Switzerland
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Castaldo, F., Palmieri, F.A.N. (2014). Data Fusion Using a Factor Graph for Ship Tracking in Harbour Scenarios. In: Bassis, S., Esposito, A., Morabito, F. (eds) Recent Advances of Neural Network Models and Applications. Smart Innovation, Systems and Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-04129-2_19
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DOI: https://doi.org/10.1007/978-3-319-04129-2_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04128-5
Online ISBN: 978-3-319-04129-2
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