Browsing by Author "Luz, S."

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Open Access
Evaluation of dominant and non-dominant hand movements for volleyball action modelling
(Association for Computing Machinery, Inc, 2019) Haider, F.; Salim, F. A.; Yengeç-Taşdemir, S. B.; Naghashi, Vahid; Tengiz, İ.; Cengiz, K.; Postma, D. B. W.; Van Delden, R.; Reidsma, D.; Van Beijnum, B. J.; Luz, S.
In this paper, we assess the use of Inertial Measurement Units (IMU) in recognising different volleyball-specific actions. Analysis of the results suggests that all sensors in the IMU (i.e. magnetometer, accelerometer, barometer and gyroscope) contribute unique information in the classification of volleyball-specific actions. We demonstrate that while the accelerometer feature set provides the best Unweighted Average Recall (UAR) overall, “decision fusion” of the accelerometer with the magnetometer improves UAR slightly from 85.86% to 86.9%. Interestingly, it is also demonstrated that the non-dominant hand provides better UAR than the dominant hand. These results are even more marked with “decision fusion”.
Open Access
A searching and automatic video tagging tool for events of interest during volleyball training sessions
(Association for Computing Machinery, Inc, 2019) Salim, F. A.; Postma, D. B. W.; Van Delden, R.; Reidsma, D.; Van Beijnum, B. -J.; Haider, F.; Luz, S.; Yengeç-Taşdemir, S. B.; Naghashi, Vahid; Tengiz, İ.; Cengiz, K.; Gao, W.; Ling-Meng, H. M.; Turk, M.; Fussell, S. R.; Schuller, B.; Song, Y.; Yu, K.
Quick and easy access to performance data during matches and training sessions is important for both players and coaches. While there are many video tagging systems available, these systems require manual effort. This paper proposes a system architecture that automatically supplements video recording by detecting events of interests in volleyball matches and training sessions to provide tailored and interactive multi-modal feedback.