Contributo in atti di convegno, 2019, ENG

Towards a forensic event ontology to assist video surveillance-based vandalism detection

Sobhani F.; Straccia U.

Queen Mary University of London, London, UK; CNR-ISTI, Pisa, Italy

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.

Italian Conference on Computational Logic (CILC-19), pp. 30–47, Trieste, Italy, June 19-21, 2019

Keywords

Forensic Event Ontology, Vandalism Detection, Description Logics, Learning

CNR authors

Straccia Umberto

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"