ML Anthology

Loitering Behaviour Detection of Boats at Sea

Jose Luis Patino, James M. Ferryman
CVPRW 2017 pp. 2169-2175
doi:10.1109/CVPRW.2017.269 /cvprw/2017/patino2017cvprw-loitering/

Abstract

We present in this paper a technique for Loitering detection based on the analysis of activity zones of the monitored area. Activity zones are learnt online employing a soft computing-based algorithm which takes as input the trajectory of object mobiles appearing on the scene. Statistical properties on zone occupancy and transition between zones makes it possible to discover abnormalities without the need to learn abnormal models beforehand. We have applied this approch to the PETS2017 IPATCH dataset and addressed the challenge on detecting skiff boats loitering around a protected ship, which eventually is attacked by the skiffs. Our results show that we can detect the suspicious behaviour on time to trigger an early warning.

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Cite

Text

Patino and Ferryman. "Loitering Behaviour Detection of Boats at Sea." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.269

Markdown

[Patino and Ferryman. "Loitering Behaviour Detection of Boats at Sea." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/patino2017cvprw-loitering/) doi:10.1109/CVPRW.2017.269

BibTeX

@inproceedings{patino2017cvprw-loitering,
  title     = {{Loitering Behaviour Detection of Boats at Sea}},
  author    = {Patino, Jose Luis and Ferryman, James M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {2169-2175},
  doi       = {10.1109/CVPRW.2017.269},
  url       = {https://mlanthology.org/cvprw/2017/patino2017cvprw-loitering/}
}