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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.08621 |
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| _version_ | 1866909493768486912 |
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| author | Lin, Tica Xiang, Ruxun Liu, Gardenia Tiwari, Divyanshu Chiang, Meng-Chia Ye, Chenjiayi Pfister, Hanspeter Zhu-Tian, Chen |
| author_facet | Lin, Tica Xiang, Ruxun Liu, Gardenia Tiwari, Divyanshu Chiang, Meng-Chia Ye, Chenjiayi Pfister, Hanspeter Zhu-Tian, Chen |
| contents | Video storytelling is essential for sports performance analysis and fan engagement, enabling sports professionals and fans to effectively communicate and interpret the spatial and temporal dynamics of gameplay. Traditional methods rely on manual annotation and verbal explanations, placing significant demands on creators for video editing skills and on viewers for cognitive focus. However, these approaches are time-consuming and often struggle to accommodate individual needs. SportsBuddy addresses this gap with an intuitive, interactive video authoring tool. It combines player tracking, embedded interaction design, and timeline visualizations to seamlessly integrate narratives and visual cues within game contexts. This empowers users to effortlessly create context-driven video stories. Since its launch, over 150 sports users, including coaches, athletes, content creators, parents and fans, have utilized SportsBuddy to produce compelling game highlights for diverse use cases. User feedback highlights its accessibility and ease of use, making video storytelling and insight communication more attainable for diverse audiences. Case studies with collegiate teams and sports creators further demonstrate SportsBuddy's impact on enhancing coaching communication, game analysis, and fan engagement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_08621 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SportsBuddy: Designing and Evaluating an AI-Powered Sports Video Storytelling Tool Through Real-World Deployment Lin, Tica Xiang, Ruxun Liu, Gardenia Tiwari, Divyanshu Chiang, Meng-Chia Ye, Chenjiayi Pfister, Hanspeter Zhu-Tian, Chen Human-Computer Interaction Video storytelling is essential for sports performance analysis and fan engagement, enabling sports professionals and fans to effectively communicate and interpret the spatial and temporal dynamics of gameplay. Traditional methods rely on manual annotation and verbal explanations, placing significant demands on creators for video editing skills and on viewers for cognitive focus. However, these approaches are time-consuming and often struggle to accommodate individual needs. SportsBuddy addresses this gap with an intuitive, interactive video authoring tool. It combines player tracking, embedded interaction design, and timeline visualizations to seamlessly integrate narratives and visual cues within game contexts. This empowers users to effortlessly create context-driven video stories. Since its launch, over 150 sports users, including coaches, athletes, content creators, parents and fans, have utilized SportsBuddy to produce compelling game highlights for diverse use cases. User feedback highlights its accessibility and ease of use, making video storytelling and insight communication more attainable for diverse audiences. Case studies with collegiate teams and sports creators further demonstrate SportsBuddy's impact on enhancing coaching communication, game analysis, and fan engagement. |
| title | SportsBuddy: Designing and Evaluating an AI-Powered Sports Video Storytelling Tool Through Real-World Deployment |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2502.08621 |