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.
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