Zor, C;
Kittler, J;
(2017)
Maritime anomaly detection in ferry tracks.
In: Bayoumi, Magdy A., (ed.)
Proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
(pp. pp. 2647-2651).
IEEE: Louisiana, USA.
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Abstract
This paper proposes a methodology for the automatic detection of anomalous shipping tracks traced by ferries. The approach comprises a set of models as a basis for outlier detection: A Gaussian process (GP) model regresses displacement information collected over time, and a Markov chain based detector makes use of the direction (heading) information. GP regression is performed together with Median Absolute Deviation to account for contaminated training data. The methodology utilizes the coordinates of a given ferry recorded on a second by second basis via Automatic Identification System. Its effectiveness is demonstrated on a dataset collected in the Solent area.
| Type: | Proceedings paper |
|---|---|
| Title: | Maritime anomaly detection in ferry tracks |
| Event: | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| ISBN-13: | 978-1-5090-4117-6 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICASSP.2017.7952636 |
| Publisher version: | http://doi.org/10.1109/ICASSP.2017.7952636 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Anomaly Detection, Gaussian Processes, Maritime Traffic, Median Absolute Deviation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067248 |
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