Multicamera trajectory analysis for semantic behaviour characterisation
Luis Patino, James M. Ferryman · 2014
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 [1] on recognising behaviours of interest around a parked vehicle, namely the abnormal behaviour of someone walking around the vehicle.