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

Authors:
Muralikrishna Sridhar;Anthony G. Cohn;David C. Hogg
Affiliations:
University of Leeds, UK, {krishna, agc, dch}@comp.leeds.ac.uk;University of Leeds, UK, {krishna, agc, dch}@comp.leeds.ac.uk;University of Leeds, UK, {krishna, agc, dch}@comp.leeds.ac.uk
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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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.