In this paper we propose an architecture for a surveillance application aimed to the automatic recognition of complex events. The main novelty of this work consists in the design of an effective and viable solution for the actual implementation of a complex automatic surveillance system that explicitly separates signal processing routines from the reasoning modules. We describe our ongoing efforts in the representation of the domain knowledge and in the development of a framework that allows the operator to easily check and update the system’s knowledge base. The taxonomical knowledge is expressed through ontologies (OWL), the event classification logic is expressed using a dedicated rule language (Jess), and the implementation is based on the java language.
[1]
Gian Luca Foresti,et al.
Representing and recognizing complex events in surveillance applications
,
2007,
2007 IEEE Conference on Advanced Video and Signal Based Surveillance.
[2]
Ramakant Nevatia,et al.
Video-based event recognition: activity representation and probabilistic recognition methods
,
2004,
Comput. Vis. Image Underst..
[3]
François Brémond,et al.
Video-understanding framework for automatic behavior recognition
,
2006,
Behavior research methods.
[4]
Ramakant Nevatia,et al.
VERL: An Ontology Framework for Representing and Annotating Video Events
,
2005,
IEEE Multim..