Abstract
In this paper we describe methods currently under investigation for learning, recognising and representing American Football plays. This is a complex spatio-temporal pattern recognition problem which we propose to solve by integrating image understanding and natural language understanding. Specifically, this paper describes the model representation used at different levels of abstraction incorporating several types of knowledge: expert knowledge, domain knowledge and spatio-temporal knowledge. We also describe a decision tree based incremental learning algorithm which combines context knowledge, attribute selection and the ageing of knowledge to keep the model representation of the plays consistent with the information extracted from the American Football video tapes.
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© 1999 Springer-Verlag London Limited
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Lazarescu, M., Venkatesh, S., West, G. (1999). Using Natural Language and Video Data to Query and Learn American Football Plays. In: Singh, S. (eds) International Conference on Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-0833-7_7
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DOI: https://doi.org/10.1007/978-1-4471-0833-7_7
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1214-3
Online ISBN: 978-1-4471-0833-7
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