Multicamera trajectory analysis for semantic behaviour characterisation

[thumbnail of avss_pets2014_centaur.pdf]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.
| Preview

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Patino, L. orcid id iconORCID: https://orcid.org/0000-0002-6716-0629 and Ferryman, J. (2014) Multicamera trajectory analysis for semantic behaviour characterisation. In: 11th IEEE International Conference on Advanced Video- and Signal-based Surveillance (AVSS2014), August 26-29, 2014, Seoul, Korea, pp. 1-6.

Abstract/Summary

In this paper we propose an innovative approach for behaviour recognition, from a multicamera environment, based on translating video activity into semantics. First, we fuse tracks from individual cameras through clustering employing soft computing techniques. Then, we introduce a higher-level module able to translate fused tracks into semantic information. With our proposed approach, we address the challenge set in PETS 2014 on recognising behaviours of interest around a parked vehicle, namely the abnormal behaviour of someone walking around the vehicle.

Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/47389
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar