Surveillance Data Deployment Scheme for Cooperative Inference based on Ontology in Wide Area Surveillance

In this paper we describe a methodology to support the modeling and deployment of surveillance data for cooperative inference in wide area surveillance on the smart camera networks. Advanced smart cameras have the ability to detect motion and track objects. Some experimental smart cameras can identify objects and extract features. Recognized features if properly structured and annotated, can be a useful source of information. This work builds a hierarchical inference data deployment structure and import related and required data to annotate rich data arriving from multiple smart cameras. Proactive deployment provides efficiency to model hierarchical area ontology. We define management policies to compare their performance for the wide area surveillance.