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arXiv · 2108.07848

Multi-task learning for jersey number recognition in Ice Hockey

Kanav Vats·Mehrnaz Fani·David A. Clausi·John Zelek
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Abstract

Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision. We have designed and implemented a multi-task learning network for jersey number recognition. In order to train a network to recognize jersey numbers, two output label representations are used (1) Holistic - considers the entire jersey number as one class, and (2) Digit-wise - considers the two digits in a jersey number as two separate classes. The proposed network learns both holistic and digit-wise representations through a multi-task loss function. We determine the optimal weights to be assigned to holistic and digit-wise losses through an ablation study. Experimental results demonstrate that the proposed multi-task learning network performs better than the constituent holistic and digit-wise single-task learning networks.

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Kanav Vats, Mehrnaz Fani, David A. Clausi, John Zelek. 2021-08-17. Multi-task learning for jersey number recognition in Ice Hockey. https://arxiv.org/abs/2108.07848

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