Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in UIST '20: Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology http://doi.acm.org/10.1145/3379337.3415591
Accepted author manuscript, 7.65 MB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Reactive Video
T2 - Adaptive Video Playback Based on User Motion for Supporting Physical Activity
AU - Clarke, Christopher
AU - Cavdir, Doga
AU - Chiu, Patrick
AU - Denoue, Laurent
AU - Kimber, Don
N1 - © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in UIST '20: Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology http://doi.acm.org/10.1145/3379337.3415591
PY - 2020/10/20
Y1 - 2020/10/20
N2 - Videos are a convenient platform to begin, maintain, or improve a ftness program or physical activity. Traditional video systems allow users to manipulate videos through specifc user interface actions such as button clicks or mouse drags, but have no model of what the user is doing and are unable to adapt in useful ways. We present adaptive video playback, which seamlessly synchronises video playback with the user’s movements, building upon the principle of direct manipulation video navigation. We implement adaptive video playback in Reactive Video, a vision-based system which supports users learning or practising a physical skill. The use of pre-existing videos removes the need to create bespoke content or specially authored videos, and the system can provide real-time guidance and feedback to better support users when learning new movements. Adaptive video playback using a discrete Bayes and particle flter are evaluated on a data set collected of participants performing tai chi and radio exercises. Results show that both approaches can accurately adapt to the user’s movements, however reversing playback can be problematic.
AB - Videos are a convenient platform to begin, maintain, or improve a ftness program or physical activity. Traditional video systems allow users to manipulate videos through specifc user interface actions such as button clicks or mouse drags, but have no model of what the user is doing and are unable to adapt in useful ways. We present adaptive video playback, which seamlessly synchronises video playback with the user’s movements, building upon the principle of direct manipulation video navigation. We implement adaptive video playback in Reactive Video, a vision-based system which supports users learning or practising a physical skill. The use of pre-existing videos removes the need to create bespoke content or specially authored videos, and the system can provide real-time guidance and feedback to better support users when learning new movements. Adaptive video playback using a discrete Bayes and particle flter are evaluated on a data set collected of participants performing tai chi and radio exercises. Results show that both approaches can accurately adapt to the user’s movements, however reversing playback can be problematic.
U2 - 10.1145/3379337.3415591
DO - 10.1145/3379337.3415591
M3 - Conference contribution/Paper
SN - 9781450375146
SP - 196
EP - 208
BT - ACM Symposium on User Interface Software and Technology (UIST)
PB - ACM
CY - New York
ER -