ML Anthology

PETS 2017: Dataset and Challenge

Jose Luis Patino, Tahir Nawaz, Tom Cane, James M. Ferryman
CVPRW 2017 pp. 2126-2132
doi:10.1109/CVPRW.2017.264 /cvprw/2017/patino2017cvprw-pets/

Abstract

This paper indicates the dataset and challenges evaluated under PETS2017. In this edition PETS continues the evaluation theme of on-board surveillance systems for protection of mobile critical assets as set in PETS 2016. The datasets include (1) the ARENA Dataset; an RGB camera dataset, as used for PETS2014 to PETS 2016, which addresses protection of trucks; and (2) the IPATCH Dataset; a multi sensor dataset, as used in PETS2016, addressing the application of multi sensor surveillance to protect a vessel at sea from piracy. The datasets allow for performance evaluation of tracking in low-density scenarios and detection of various surveillance events ranging from innocuous abnormalities to dangerous and criminal situations. Training data for tracking algorithms is released with the dataset; tracking data is also available for authors addressing only surveillance event detection challenges but not working on tracking.

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Cite

Text

Patino et al. "PETS 2017: Dataset and Challenge." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.264

Markdown

[Patino et al. "PETS 2017: Dataset and Challenge." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/patino2017cvprw-pets/) doi:10.1109/CVPRW.2017.264

BibTeX

@inproceedings{patino2017cvprw-pets,
  title     = {{PETS 2017: Dataset and Challenge}},
  author    = {Patino, Jose Luis and Nawaz, Tahir and Cane, Tom and Ferryman, James M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {2126-2132},
  doi       = {10.1109/CVPRW.2017.264},
  url       = {https://mlanthology.org/cvprw/2017/patino2017cvprw-pets/}
}