AI 中文总结
研究如何在体育视频中创作动态叙事可视化，以游泳视频为案例，通过自动化管道提取数据、分析得出叙事结构并设计技术探针支持创作，经评估检验其益处与挑战。
AI 中文摘要
我们以游泳比赛为案例研究，通过自动化数据准备、系统分析、技术探针设计和评估，探讨如何支持在体育视频中创作动态叙事可视化。体育视频在社交媒体广泛传播，内容创作者希望向普通观众呈现和解释复杂赛事。动态可视化是嵌入数据的有效方式，但现有方法主要关注嵌入，缺乏对创作叙事的探索。我们以游泳视频为理想案例，开发自动化管道提取结构化数据，通过观察分析得出叙事结构，设计技术探针支持创作。我们用有经验的内容创作者和/或平面设计师评估该方法，以检验创作动态叙事可视化的益处和挑战。所有补充材料在补充材料指针部分描述并可在OSF获取：此http链接。
英文摘要
We investigate how to support authoring narrative visualizations in motion in sports videos, drawing on automated data preparation, systematic analysis, technology probe design, and evaluation, using swimming races as a case study. Sports videos are widely broadcast and shared across social media, where content creators increasingly seek to present and explain complex events to general audiences. Visualization in motion has been explored as an efficient way to embed data into videos and to move with the data referents, providing additional information and helping audiences understand races. However, existing approaches primarily focus on embedding visualizations in videos, lacking exploration of how to support authoring narratives that coordinate views, data, and temporal progression to explain the unfolding races. To address this gap, we use swimming videos as an ideal case for exploration, as swimming is a sport with rich, dynamic data and visualizations in practice. We develop an automated pipeline that extracts structured data from videos, derive narrative constructs through observational analysis of sports broadcasts, and design a technology probe that supports authoring using data prepared by our pipeline and narrative constructs derived from our observations. We evaluate our approach with experienced content creators and/or graphic designers to examine the benefits and challenges of authoring narrative visualizations in motion. All supplemental materials are described in the Supplemental Material Pointers section and are on OSF: osf.io/bq47n/.
