Abstract
Video plays a crucial role in sports training, enabling participants to analyze their movements and identify opponents' weaknesses. Despite the easy access to sports videos, the rich motion data within them remains underutilized due to the lack of clear performance indicators and discrepancies from real-game conditions. To address this, we employed advanced computer vision algorithms to reconstruct human motions in an immersive environment, where users can freely observe and interact with the movements. Basketball shooting was chosen as a representative scenario to validate this framework, given its fast pace and extensive physical contact. Collaborating with experts, we iteratively designed motion-related visualizations to improve the understanding of complex movements. A one-on-one matchup simulating real games was also provided, allowing users to compete directly with the reconstructed motions. Our user studies demonstrate that this method enhances participants' movement comprehension and engagement, while insights derived from interviews inform future immersive training designs.
| Original language | English |
|---|---|
| Title of host publication | UIST 2025 - Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology |
| Editors | Andrea Bianchi, Elena L. Glassman, Wendy E. Mackay, Shengdong Zhao, Ian Oakley, Jeeeun Kim |
| Publisher | Association for Computing Machinery, Inc |
| ISBN (Electronic) | 9798400720376 |
| DOIs | |
| Publication status | Published - 27 Sept 2025 |
| Event | 38th Annual ACM Symposium on User Interface Software and Technology, UIST 2025 - Busan, Korea, Republic of Duration: 28 Sept 2025 → 1 Oct 2025 |
Conference
| Conference | 38th Annual ACM Symposium on User Interface Software and Technology, UIST 2025 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Busan |
| Period | 28/09/25 → 1/10/25 |
Keywords
- Immersive Training
- Mixed Reality
- SportsXR
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