PETS2025: multi-authority multi-sensor maritime surveillance challenge and evaluation

Markchom, T. ORCID: https://orcid.org/0000-0002-2685-0738, Boyle, J. ORCID: https://orcid.org/0000-0002-5785-8046, Chen, L., Ferryman, J., Marturini, M., Veigl, S., Opitz, A., Kriechbaum-Zabini, A., Bratskas, R., Gkamaris, A., Papachristos, D., Leventakis, G., Fan, W., Huang, H.-W., Hwang, J.-N., Kim, P., Kim, K., Huang, C.-I., Saito, K., Kaneko, S., Sudo, K., Thanh Thien, N., Kao, M.-Y., Hsieh, J.-W., Lilek, T., Pomsuwan, T., Gu, J., Xu, T., Zhu, X., Wu, X., Kittler, J., Stacy, S., Gabaldon, A., Tu, P., Kim, S., Kim, D. and Lee, K. (2025) PETS2025: multi-authority multi-sensor maritime surveillance challenge and evaluation. In: IEEE International Conference on Advanced Visual and Signal-Based Systems (AVSS 2025), 11-13 August 2025, Tainan, Taiwan. doi: 10.1109/AVSS65446.2025.11149786

Abstract/Summary

This paper presents the outcomes of the PETS2025 challenge, held in conjunction with AVSS 2025 and sponsored by the EU-funded EURMARS project. The challenge introduces a novel maritime surveillance dataset comprising image sequences captured by diverse multi-altitude, multimodal sensors, reflecting the real-world multi-authority environment. The key tasks include: (1) object detection using various sensors across different platforms (ground-based and low-altitude aerial) and spectral ranges (visible, thermal, ultraviolet (UV), and short-wave infrared (SWIR)); (2) long-term tracking of targets in maritime environments spanning both sea and land; and (3) approximating target geolocations by using sensor imagery and telemetry data. Performance evaluations of results submitted by 12 international participants are discussed. The results show the effectiveness of these submissions and highlight ongoing challenges posed by heterogeneous sensors and complex environments. These challenges emphasise the need to further improve detection, tracking, and geolocation approximation for maritime and coastal surveillance.

Item Type	Conference or Workshop Item (Paper)
URI	https://centaur.reading.ac.uk/id/eprint/124177
Identification Number/DOI	10.1109/AVSS65446.2025.11149786
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
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