  The detection and representation of events is a critical element in automated
surveillance systems. We present here an ontology for representing complex
semantic events to assist video surveillance-based vandalism detection. The
ontology contains the definition of a rich and articulated event vocabulary
that is aimed at aiding forensic analysis to objectively identify and represent
complex events. Our ontology has then been applied in the context of London
Riots, which took place in 2011. We report also on the experiments conducted to
support the classification of complex criminal events from video data.
