Abstract
This paper presents a method to perform team activity recognition in handball videos by using low level motion related features (position and direction of the motion), where a tracking process is not needed. Bag-of-words and topic modeling-based techniques have been used to characterize each video clip. Several parameter configurations have been tested to select the ones producing the best performance. An ensemble of selected classifiers has been constructed to obtain an overall accuracy rate of 98.38% in the recognition task among four different team activities.
The authors acknowledge the Fundació Caixa-Castelló Bancaixa under project P1-1A2010-11.
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Rodríguez-Pérez, S., Montoliu, R. (2013). Bag-of-Words and Topic Modeling-Based Sport Video Analysis. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_22
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DOI: https://doi.org/10.1007/978-3-642-38628-2_22
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