avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality
<|reference_start|>avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality: Table tennis stroke training is a critical aspect of player development. We designed a new augmented reality (AR) system, avaTTAR, for table tennis stroke training. The system provides both "on-body" (first-person view) and "detached" (third-person view) visual cues, enabling users to visualize target strokes and correct their attempts effectively with this dual perspectives setup. By employing a combination of pose estimation algorithms and IMU sensors, avaTTAR captures and reconstructs the 3D body pose and paddle orientation of users during practice, allowing real-time comparison with expert strokes. Through a user study, we affirm avaTTAR's capacity to amplify player experience and training results.<|reference_end|>
@article{ma2024avattar:,
    title={avaTTAR: Table Tennis Stroke Training with On-body and Detached
  Visualization in Augmented Reality},
    author={Dizhi Ma, Xiyun Hu, Jingyu Shi, Mayank Patel, Rahul Jain, Ziyi Liu,
  Zhengzhe Zhu and Karthik Ramani},
    journal={UIST '2024: Proceedings of the 37th Annual ACM Symposium on User
  Interface Software and Technology},
    year={2024},
    doi={10.1145/3654777.3676400},
    archivePrefix={arXiv},
    eprint={2407.15373},
    primaryClass={cs.HC}
}