Semantic web technologies for video surveillance metadata

Abstract

Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach.

A Semantic Autonomous Video Surveillance System for Dense Camera Networks in Smart Cities

“…However, these approaches only use semantic technologies for characterizing information. Zhang et al [ 43 , 44 ] and Marraud et al [ 45 ] in their studies, use semantics to allow advanced queries based on video features to databases; François et al [ 46 ] propose a new language for the representation of events in a video to facilitate searches, and Poppe et al [ 47 ] report about a system to unify the video surveillance semantic information. That means that they employ some other approach to identify objects and alarms, and then use semantic technologies only to represent that information.…”