Towards a Forensic Event Ontology to Assist Video Surveillance-based Vandalism Detection
This work addresses the need for objective forensic analysis in video surveillance for vandalism detection, but it appears incremental as it builds on existing ontology methods for a specific domain.
The authors tackled the problem of automated surveillance by developing an ontology to represent complex semantic events for vandalism detection, applying it to the 2011 London Riots and reporting on experiments for classifying criminal events from video data.
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.