Embedding data visualizations in video can enhance the communication of complex information. However, this process is often labor-intensive, requiring designers to adjust visualizations frame by frame manually. In this work, we present ChartBlender, a novel system that streamlines this process by enabling users to create data visualizations, embed them seamlessly into video scenes, and automatically synchronize them with both camera motion and moving objects. Particularly, ChartBlender incorporates a tracking algorithm that supports both object and camera tracking, ensuring robust alignment of visualizations with dynamic video content. To maintain visual clarity and aesthetic coherence, we also explore the design space of video-suited visualizations and develop a library of customizable templates optimized for video embedding. We evaluate \oursName\ChartBlender through two controlled experiments and expert interviews with five domain experts. Results show that our system enables accurate synchronization and accelerates the production of data-driven videos.

翻译：在视频中嵌入数据可视化可增强复杂信息的传达效果。然而，这一过程通常需要大量人工操作，要求设计者逐帧手动调整可视化效果。本文提出ChartBlender，一种通过支持用户创建数据可视化、将其无缝嵌入视频场景、并使其与摄像机运动及移动对象自动同步，从而简化该流程的新型系统。特别地，ChartBlender集成了一种同时支持对象跟踪与摄像机跟踪的追踪算法，确保可视化内容与动态视频素材的鲁棒对齐。为保持视觉清晰度与美学一致性，我们还探索了适用于视频的可视化设计空间，并开发了一个针对视频嵌入优化的可定制模板库。我们通过两项受控实验及与五位领域专家的访谈对ChartBlender进行评估。结果表明，本系统能够实现精确同步并加速数据驱动视频的制作。