Automatic surveillance systems for the maritime domain are becoming more and more important due to a constant increase of naval traffic and to the simultaneous reduction of crews on decks. However, available technology still provides only a limited support to this kind of applications. In this paper, a modular system for intelligent maritime surveillance, capable of fusing information from heterogeneous sources, is described. The system is designed to enhance the functions of the existing Vessel Traffic Services systems and to be deployable in populated areas, where radar-based systems cannot be used due to the high electromagnetic radiation emissions. A quantitative evaluation of the proposed approach has been carried out on a large and publicly available data set of images and videos, collected from multiple real sites, with different light, weather, and traffic conditions.

Enhancing automatic maritime surveillance systems with visual information / Bloisi, Domenico Daniele; Previtali, Fabio; Pennisi, Andrea; Nardi, Daniele; Fiorini, Michele. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - STAMPA. - 18:4(2017), pp. 824-833. [10.1109/TITS.2016.2591321]

Enhancing automatic maritime surveillance systems with visual information

BLOISI, Domenico Daniele
;
PREVITALI, FABIO
;
PENNISI, ANDREA
;
NARDI, Daniele
;
2017

Abstract

Automatic surveillance systems for the maritime domain are becoming more and more important due to a constant increase of naval traffic and to the simultaneous reduction of crews on decks. However, available technology still provides only a limited support to this kind of applications. In this paper, a modular system for intelligent maritime surveillance, capable of fusing information from heterogeneous sources, is described. The system is designed to enhance the functions of the existing Vessel Traffic Services systems and to be deployable in populated areas, where radar-based systems cannot be used due to the high electromagnetic radiation emissions. A quantitative evaluation of the proposed approach has been carried out on a large and publicly available data set of images and videos, collected from multiple real sites, with different light, weather, and traffic conditions.
2017
Automotive Engineering; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition
01 Pubblicazione su rivista::01a Articolo in rivista
Enhancing automatic maritime surveillance systems with visual information / Bloisi, Domenico Daniele; Previtali, Fabio; Pennisi, Andrea; Nardi, Daniele; Fiorini, Michele. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - STAMPA. - 18:4(2017), pp. 824-833. [10.1109/TITS.2016.2591321]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/933165
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