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PETS 2016: dataset and challenge

Patino, L., Cane, T., Vallee, A. and Ferryman, J. (2016) PETS 2016: dataset and challenge. In: IEEE Cnference on Computer Vision and Pattern Recognition Workshops (CVPRW), 26 June-1 July 2016, Las Vegas, USA, pp. 1240-1247.

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Official URL: https://doi.org/10.1109/CVPRW.2016.157

Abstract/Summary

This paper describes the datasets and computer vision challenges that form part of the PETS 2016 workshop. PETS 2016 addresses the application of on-board multi sensor surveillance for protection of mobile critical assets. The sensors (visible and thermal cameras) are mounted on the asset itself and surveillance is performed around the asset. Two datasets are provided: (1) a multi sensor dataset as used for the PETS2014 challenge which addresses protection of trucks (the ARENA Dataset); and (2) a new dataset - the IPATCH Dataset - addressing the application of multisensor surveillance to protect a vessel at sea from piracy. The dataset specifically addresses several vision challenges set in the PETS 2016 workshop, and corresponding to different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘simple’ event detection: the behaviour recognition of a single actor) and High-Level Video Analysis (‘complex’ event detection: the behaviour and interaction recognition of several actors).

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:68996

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