TY - GEN
T1 - Shot detection in racket sport video at the frame level using a recurrent neural network
AU - Horie, Shuto
AU - Sato, Yuji
AU - Furuyama, Junko
AU - Tanabiki, Masamoto
AU - Aoki, Yoshimitsu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - In recent years, there has been a demand in the sports industry to reduce the burden of data collection and video editing for tactical analysis. To achieve these, a system that can recognize the game context is needed. In this study, we proposed a method to identify the player's shot timing at the frame level during a ball-striking sport. In this study, players' shots were detected in video of a tennis match. It was shown that shots could be detected with an F-score value of 87% or more within an error range of 1 frame (0.033 sec) by considering time-series information using a recurrent neural network. This technology is expected to be applied not only to tennis, but also to other sports that involve ball shots, such as table tennis, baseball, and volleyball. At the same time, it can be used to detect moments of a specific action (for example, touching or hitting an object).
AB - In recent years, there has been a demand in the sports industry to reduce the burden of data collection and video editing for tactical analysis. To achieve these, a system that can recognize the game context is needed. In this study, we proposed a method to identify the player's shot timing at the frame level during a ball-striking sport. In this study, players' shots were detected in video of a tennis match. It was shown that shots could be detected with an F-score value of 87% or more within an error range of 1 frame (0.033 sec) by considering time-series information using a recurrent neural network. This technology is expected to be applied not only to tennis, but also to other sports that involve ball shots, such as table tennis, baseball, and volleyball. At the same time, it can be used to detect moments of a specific action (for example, touching or hitting an object).
KW - Shot Detection
KW - Sports Video Analysis
KW - Tennis
UR - http://www.scopus.com/inward/record.url?scp=85084858481&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084858481&partnerID=8YFLogxK
U2 - 10.1109/SITIS.2019.00078
DO - 10.1109/SITIS.2019.00078
M3 - Conference contribution
AN - SCOPUS:85084858481
T3 - Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
SP - 447
EP - 453
BT - Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
A2 - Yetongnon, Kokou
A2 - Dipanda, Albert
A2 - Sanniti di Baja, Gabriella
A2 - Gallo, Luigi
A2 - Chbeir, Richard
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
Y2 - 26 November 2019 through 29 November 2019
ER -