SWAV: semantics-based workflows for automatic video analysis

Authors:
Gayathri Nadarajan;Yun-Heh Chen-Burger;Robert B. Fisher
Affiliations:
School of Informatics, University of Edinburgh, UK;School of Informatics, University of Edinburgh, UK;School of Informatics, University of Edinburgh, UK
Venue:
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Year:
2011

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KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
Semantics and Planning Based Workflow Composition for Video Processing

Journal of Grid Computing

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Abstract

This paper outlines the SWAV system - Semantics-based Workflows for Automatic Video Analysis. SWAV utilises ontologies and planning as core technologies to gear the composition and execution of video processing workflows. It is tailored for users without image processing expertise who have specific goals (tasks) and restrictions on these goals but not the ability to choose appropriate video processing software to solve their goals. An evaluation on a set of ecological videos has indicated that SWAV: 1) is more time-efficient at solving video classification tasks than manual processing; 2) is more adaptable in response to changes in user requests (task restrictions and video descriptions) than modifying existing image processing programs; and 3) assists the user in selecting optimal solutions by providing recommended descriptions.