Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908441901006848 |
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| author | Phosanarack, Mathieu Wallard, Laura Lepreux, Sophie Kolski, Christophe Avril, Eugénie |
| author_facet | Phosanarack, Mathieu Wallard, Laura Lepreux, Sophie Kolski, Christophe Avril, Eugénie |
| contents | Markerless Motion Capture (MoCap) using smartphone cameras is a promising approach to making exergames more accessible and cost-effective for health and rehabilitation. Unlike traditional systems requiring specialized hardware, recent advancements in AI-powered pose estimation enable movement tracking using only a mobile device. For an upcoming study, a mobile application with real-time exergames including markerless motion capture is being developed. However, implementing such technology introduces key challenges, including balancing accuracy and real-time responsiveness, ensuring proper user interaction. Future research should explore optimizing AI models for realtime performance, integrating adaptive gamification, and refining user-centered design principles. By overcoming these challenges, smartphone-based exergames could become powerful tools for engaging users in physical activity and rehabilitation, extending their benefits to a broader audience. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_06669 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs Phosanarack, Mathieu Wallard, Laura Lepreux, Sophie Kolski, Christophe Avril, Eugénie Human-Computer Interaction Markerless Motion Capture (MoCap) using smartphone cameras is a promising approach to making exergames more accessible and cost-effective for health and rehabilitation. Unlike traditional systems requiring specialized hardware, recent advancements in AI-powered pose estimation enable movement tracking using only a mobile device. For an upcoming study, a mobile application with real-time exergames including markerless motion capture is being developed. However, implementing such technology introduces key challenges, including balancing accuracy and real-time responsiveness, ensuring proper user interaction. Future research should explore optimizing AI models for realtime performance, integrating adaptive gamification, and refining user-centered design principles. By overcoming these challenges, smartphone-based exergames could become powerful tools for engaging users in physical activity and rehabilitation, extending their benefits to a broader audience. |
| title | Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.06669 |