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Semi-supervised vision-based maritime surveillance system using fused visual attention maps

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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, without making any assumptions about environmental or visual conditions. The offline initialization is based on large graph semi-supervised technique. 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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Notes

  1. http://www.poseidonproject.gr/

  2. https://github.com/konstmakantasis/Poseidon

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Acknowledgments

The work has been partially supported by IKY Fellowships of excellence for postgraduate studies in Greece–Siemens program. The work has, also, been supported by European Union funds and national funds from Greece and Cyprus under the project POSEIDON: Development of an Intelligent System for Coast Monitoring using Camera Arrays and Sensor Networks in the context of the inter-regional programme INTERREG (Greece-Cyprus cooperation) - contract agreement K1 3 1017/6/2011.

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Authors and Affiliations

  1. Technical University of Crete, Chania, Greece

    Konstantinos Makantasis, Eftychios Protopapadakis & Nikolaos Matsatsinis

  2. National Technical University of Athens, Athens, Greece

    Anastasios Doulamis

Authors
  1. Konstantinos Makantasis
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  2. Eftychios Protopapadakis
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  3. Anastasios Doulamis
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  4. Nikolaos Matsatsinis
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Correspondence to Eftychios Protopapadakis.

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Makantasis, K., Protopapadakis, E., Doulamis, A. et al. Semi-supervised vision-based maritime surveillance system using fused visual attention maps. Multimed Tools Appl 75, 15051–15078 (2016). https://doi.org/10.1007/s11042-015-2512-x

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  • DOI: https://doi.org/10.1007/s11042-015-2512-x

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