avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866913552406675456 |
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| author | Ma, Dizhi Hu, Xiyun Shi, Jingyu Patel, Mayank Jain, Rahul Liu, Ziyi Zhu, Zhengzhe Ramani, Karthik |
| author_facet | Ma, Dizhi Hu, Xiyun Shi, Jingyu Patel, Mayank Jain, Rahul Liu, Ziyi Zhu, Zhengzhe Ramani, Karthik |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15373 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality Ma, Dizhi Hu, Xiyun Shi, Jingyu Patel, Mayank Jain, Rahul Liu, Ziyi Zhu, Zhengzhe Ramani, Karthik Human-Computer Interaction 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. |
| title | avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2407.15373 |