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Temporal segmentation and recognition of team activities in sports

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Abstract

A method for temporal segmentation and recognition of team activities in sports, based on a new activity feature extraction, is presented. Given the positions of team players from a plan view of the playground at any given time, we generate a smooth distribution on the whole playground, termed the position distribution of the team. Computing the position distribution for each frame provides a sequence of distributions, which we process to extract motion features for activity recognition. We can classify six different team activities in European handball and eight different team activities in field hockey datasets. The field hockey dataset is a new, large and challenging dataset that is presented for the first time for continuous segmentation of team activities. Our approach is different from other trajectory-based methods. These methods extract activity features using the explicitly defined trajectories, where the players have specific positions. In our work, given the specific positions of the team players at a frame, we construct a position distribution for the team on the whole playground and process the sequence of position distribution images to extract activity features. Extensive evaluation and results show that our approach is effective.

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Acknowledgements

This work is supported by Science Foundation Ireland under Grant 07/CE/I114. The authors would like to acknowledge Disney Research Pittsburgh for their help in constructing the camera network around the field hockey playground in Ireland. We also would like to thank Statsports for supplying us GPS sensors, and finally, we thank Irish Hockey Association for their collaboration to collect the field hockey dataset.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Middle East Technical University - Northern Cyprus Campus, via Mersin 10, Turkey

    Cem Direkoǧlu

  2. INSIGHT Centre, Dublin City University, Dublin, Ireland

    Noel E. O’Connor

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  1. Cem Direkoǧlu
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  2. Noel E. O’Connor
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Correspondence to Cem Direkoǧlu.

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Direkoǧlu, C., O’Connor, N.E. Temporal segmentation and recognition of team activities in sports. Machine Vision and Applications 29, 891–913 (2018). https://doi.org/10.1007/s00138-018-0944-9

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  • DOI: https://doi.org/10.1007/s00138-018-0944-9

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