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

Area of Science:

• Human-Computer Interaction
• Sports Analytics
• Video Processing

Background:

• Current TV broadcasts selectively embed visualizations in sports videos for audience engagement.
• Existing methods lack flexibility and customization in visualization timing and content.

Purpose of the Study:

• To develop a flexible framework for embedding visualizations in sports videos, specifically swimming.
• To enable dynamic and customized visualization arrangements beyond current broadcast standards.

Main Methods:

• Systematic review of TV broadcast practices for visualization patterns.
• Formative study with the general population to gather broader design perspectives.
• Development of a configuration framework and a technology probe (SwimChrono).

Main Results:

• Identified recurring patterns of visualization and competition status in broadcasts.
• Designed a framework for formally specifying visualization timing based on swimming context metadata.
• SwimChrono demonstrated adaptable and novel visualization arrangements through user-customized configurations.

Conclusions:

• The proposed framework offers a flexible approach to embedding visualizations in sports videos.
• It supports novel, adaptable, and audience-customized visualization arrangements for diverse swimming contexts.
• The technology probe and use cases illustrate the framework's practical applicability.