Multicamera trajectory analysis for semantic behaviour characterisation

Patino, L. ORCID: 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), 2014-08-26, 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.