Abstract
This paper presents a prototype of a tennis movie retrieval system and a recognition method using a deep learning for detecting user’s swing motions of a tennis racket. Our system leverages 3-axes acceleration data of swing motions obtained from a sensor device so that a user can retrieve the required tennis movies by intuitive swing motions with the sensor device. In our approach, the user’s swing motion is segmented into three parts: pre-hit part, hit part, and post-hit part, for making the learning data. To implement such a gesture-based tennis movie retrieval system, we defined 57 swing motions where swing speed is considered as well.
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Tsukiji, H., Chi, H., Takano, K., Li, K.F. (2019). Classification of Tennis Swing Motions Using Deep Learning. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham. https://doi.org/10.1007/978-3-319-93659-8_105
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DOI: https://doi.org/10.1007/978-3-319-93659-8_105
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