This paper proposes a real-time system capable to extract andmodel object trajectories from a multi-camera setup with theaim of identifying abnormal paths. The trajectories are modeledas a sequence of positional distributions (2D Gaussians)and clustered in the training phase by exploiting an innovativedistance measure based on a global alignment techniqueand Bhattacharyya distance between Gaussians. An on-lineclassification procedure is proposed in order to on-the-fly classifynew trajectories into either “normal” or “abnormal” (in thesense of rarely seen before, thus unusual and potentially interesting).Experiments on a real scenario will be presented.

A Real-Time System for Abnormal Path Detection / Calderara, Simone; C., Alaimo; Prati, Andrea; Cucchiara, Rita. - ELETTRONICO. - (2009), pp. 1-6. ((Intervento presentato al convegno 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP-09) tenutosi a London (UK) nel 3 December 2009.

I documenti presenti in Iris Unimore sono rilasciati con licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia, salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Powered by IRIS-about IRIS-Utilizzo dei cookie

 Copyright © 2020