Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

• Autor principal: Gomez Alvarado, H. (author)
• Otros Autores: Arias Tapia, S. (author)
• Formato: article
• Publicado: 2013
• Materias: high; level activities; video scene understanding; human behaviour recognition; video; surveillance; multi; sensory surveillance; ontology; based recognition
• Acceso en línea: http://dx.doi.org/10.1080/00207721.2013.801095; http://dspace.utpl.edu.ec/handle/123456789/19197