Kosuke Sato
ABSTRACT
A block machine has been proposed as effective systems to support attack practice in volleyball. A method for manipulating the system by tablet operation has been established, and the use of the system has been shown to improve practice effectiveness. However, due to the requirement of manual operation, it has been reported that the efficiency of practice decreases due to the error between the block position and the attack position. Therefore, in order to operate the block machine automatically, we propose a method to acquire the player position from monocular video in real time and predict the attack position.
Supplemental Material
- H. C. Miles, S. R. Pop, S. J. Watt, G. P. Lawrence and N. W. John. 2012. A review of virtual environments for training in ball sports. Computers & Graphics 36, 6 (2012), 714--726. Google Scholar
Digital Library
- J. Stoev, S. Gillijns, A. Bartic, and W. Symens. 2010. Badminton playing robot - a multidisciplinary test case in mechatronics, IFAC 43, 18 (2010), 725--731.Google Scholar
- K. Sato, K. Watanabe, S. Mizuno, M. Manabe, H. Yano, and H. Iwata. 2017. Development of a block machine for volleyball attack training. IEEE ICRA (2017), 1036--1041.Google Scholar
- K. Sato, K. Watanabe, S. Mizuno, M. Manabe, H. Yano, and H. Iwata. 2017. Development and assessment of a block machine for volleyball attack training. Advanced Robotics 31, 21 (2017), 1144--1156.Google ScholarCross Ref
- Z. Cao, T. Simon, S. Wei, and Y. Sheikh. 2017. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. IEEE CVPR (2017), 1302--1310.Google Scholar
Index Terms
- Motion recognition for automatic control of a block machine
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