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Discovering an Event Taxonomy from Video using Qualitative Spatio-temporal Graphs

Sridhar, M, Cohn, AG and Hogg, DC (2010) Discovering an Event Taxonomy from Video using Qualitative Spatio-temporal Graphs. In: Coelho, H, Suder, R and Wooldridge, M, (eds.) ECAI 2010 - 19th European Conference on Artificial Intelligence,Proceedings. 19th European Conference on Artificial Intelligence, 16-20 August 2010, Lisbon, Portugal. IOS Press , 1103 - 1104 . ISBN 978-1-60750-605-8

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Abstract

This work proposes a graph mining based approach to mine a taxonomy of events from activities for complex videos which are represented in terms of qualitative spatio-temporal relationships. A Hidden Markov Model to obtain stable qualitative spatial relations from noisy measurements is introduced. The effectiveness of the approach is demonstrated through experimental results for a complex aircraft turnaround apron scenario.

Item Type: Proceedings Paper
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds)
The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 29 Oct 2012 14:59
Last Modified: 08 Feb 2013 17:40
Published Version: http://dx.doi.org/10.3233/978-1-60750-606-5-1103
Status: Published
Publisher: IOS Press
Identification Number: 10.3233/978-1-60750-606-5-1103
URI: http://eprints.whiterose.ac.uk/id/eprint/74699

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