Towards a Forensic Event Ontology to Assist Video Surveillance-based Vandalism Detection

Tracking #: 1721-2933

This paper is currently under review
Authors: 
Faranak Sobhani
Umberto Straccia
Qianni Zhang

Responsible editor: 
Krzysztof Janowicz

Submission type: 
Ontology Description
Abstract: 
Following the exponential deployment of surveillance systems across a wide-spread region of geographic locations, detection and representation of events have become a critical element in automated surveillance systems. We present here an ontology framework for representing complex semantic events to aid video surveillance-based vandalism detection. The proposed ontology builds on DOLCE ontology and relies on the linguistic and cognitive modelling of philosophical knowledge to achieve interoperability between proprietary surveillance systems. The explicit definition of event vocabulary we present here is aimed at aiding forensic analysis to objectively identify and represent complex events. The proposed ontology has then been applied in the context of London Riots, which took place in 2011, and we report also on the experiments conducted to support the classification of complex criminal events.
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