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Authors: Eftychios Protopapadakis 1 ; Konstantinos Makantasis 1 and Nikolaos Doulamis 2

Affiliations: 1 Technical University of Crete, Greece ; 2 National Technical University of Athens, Greece

Keyword(s): Vision-based System, Maritime Surveillance, Semi-supervised Learning, Visual Attention Maps, Vehicle Tracking.

Abstract: This paper presents a vision-based system for maritime surveillance, using moving PTZ cameras. The proposed methodology fuses a visual attention method that exploits low-level image features appropriately selected for maritime environment, with appropriate tracker. Such features require no assumptions about environmental nor visual conditions. The offline initialization is based on large graph semi-supervised technique in order to minimize user’s effort. System’s performance was evaluated with videos from cameras placed at Limassol port and Venetian port of Chania. Results suggest high detection ability, despite dynamically changing visual conditions and different kinds of vessels, all in real time.

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Paper citation in several formats:
Protopapadakis, E.; Makantasis, K. and Doulamis, N. (2015). Maritime Targets Detection from Ground Cameras Exploiting Semi-supervised Machine Learning. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 583-594. DOI: 10.5220/0005456205830594

@conference{mms-er3d15,
author={Eftychios Protopapadakis. and Konstantinos Makantasis. and Nikolaos Doulamis.},
title={Maritime Targets Detection from Ground Cameras Exploiting Semi-supervised Machine Learning},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D},
year={2015},
pages={583-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005456205830594},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D
TI - Maritime Targets Detection from Ground Cameras Exploiting Semi-supervised Machine Learning
SN - 978-989-758-090-1
IS - 2184-4321
AU - Protopapadakis, E.
AU - Makantasis, K.
AU - Doulamis, N.
PY - 2015
SP - 583
EP - 594
DO - 10.5220/0005456205830594
PB - SciTePress

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