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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7



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ISSN 2083-6473
ISSN 2083-6481 (electronic version)
 

 

 

Editor-in-Chief

Associate Editor
Prof. Tomasz Neumann
 

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@umg.edu.pl
Computer Vision and Ship Traffic Analysis: Inferring Maneuver Patterns From the Automatic Identification System
1 Norwegian University of Science and Technology, Trondheim, Norway
ABSTRACT: The Automatic Identification System has proven itself as a valuable source for ship traffic information. Its introduction has reversed the previous situation with scarcity of precise data from ship traffic and has instead posed the reverse challenge of coping with an overabundance of data. The number of time series available for ship manoeuvring analysis has increased from tens, or hundreds, to several thousands. Sifting through this data manually, either to find the salient features of traffic, or to provide statistical distributions of decision variables is an extremely time consuming procedure. In this paper we present the results of applying computer vision techniques to this problem and show how it is possible to automatically separate AIS data in order to obtain traffic statistics and prevailing features down to the scale of individual manoeuvres and how this procedure enables the production of a simplified model of ship traffic.
REFERENCES
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Citation note:
Aarsæther K.G., Moan T.: Computer Vision and Ship Traffic Analysis: Inferring Maneuver Patterns From the Automatic Identification System. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 4, No. 3, pp. 303-308, 2010
Authors in other databases:
Torgeir Moan: Scholar iconsSepcmIAAAAJ

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