Skip to main navigation Skip to search Skip to main content

Diving Deep into Time: Temporal Arrangements for Embedded Visualization in Swimming Videos

  • Junxiu Tang
  • , Lijie Yao*
  • , Lu Ying
  • , Romain Vuillemot
  • , Petra Isenberg
  • *Corresponding author for this work
  • Northwestern University
  • National University of Singapore
  • LIRIS Lab.
  • Université Paris-Saclay

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce a temporal arrangement framework for embedding visualizations in sports videos with a focus on swimming. Our work is inspired by strategies used in current TV broadcasts, where visualizations are selectively displayed to provide meaningful and engaging information to audiences. We began with a systematic review of TV broadcast practices, through which we identified recurring temporal combinations of visualizations and competition statuses, which we define as patterns of temporal arrangement for embedded visualizations. To move beyond the constraints of existing broadcast practices, we then conducted a formative study with a general population. Based on this broader perspective, we designed a configuration framework that allows us to formally specify when and for how long, related to swimming context metadata, visualizations appear in a video. We instantiate the framework in a technology probe, SwimChrono, for applications with real-world swimming context videos. Through audience-customized configurations, SwimChrono supports novel arrangements beyond those used in existing professional settings, is adaptable to various swimming contexts, including different lengths and swimming styles, and key events. Furthermore, we conduct user studies and contribute use cases to illustrate how our framework can be well applied for diverse needs.

Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalIEEE Transactions on Visualization and Computer Graphics
DOIs
Publication statusAccepted/In press - 2026

Keywords

  • augmented sports video
  • design pattern
  • Embedded visualization
  • sports visualization
  • visualization in motion

Cite this