Unidentified Floating Object Detection in Maritime Environment

Darshan Venkatrayappa, Agnès Desolneux, Jean-Michel Hubert, Josselin Manceau

2022

Abstract

In this article, we present a new unsupervised approach to detect unidentified floating objects in the maritime environment. The proposed approach is capable of detecting floating objects online without any prior knowledge of their visual appearance, shape or location. Given an image from a video stream, we extract the self-similar and dissimilar components of the image using a visual dictionary. The dissimilar component consists of noise and structures (objects). The structures (objects) are then extracted using an a contrario model. We demonstrate the capabilities of our algorithm by testing it on videos exhibiting varying maritime scenarios.

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Paper Citation


in Harvard Style

Venkatrayappa D., Desolneux A., Hubert J. and Manceau J. (2022). Unidentified Floating Object Detection in Maritime Environment. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-555-5, pages 65-74. DOI: 10.5220/0010771800003124


in Bibtex Style

@conference{visapp22,
author={Darshan Venkatrayappa and Agnès Desolneux and Jean-Michel Hubert and Josselin Manceau},
title={Unidentified Floating Object Detection in Maritime Environment},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2022},
pages={65-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010771800003124},
isbn={978-989-758-555-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Unidentified Floating Object Detection in Maritime Environment
SN - 978-989-758-555-5
AU - Venkatrayappa D.
AU - Desolneux A.
AU - Hubert J.
AU - Manceau J.
PY - 2022
SP - 65
EP - 74
DO - 10.5220/0010771800003124