RouteFlow: Trajectory-Aware Animated Transitions

Duan Li, Xinyuan Guo, Xinhuan Shu, Lanxi Xiao, Lingyun Yu, Shixia Liu*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

Animating objects' movements is widely used to facilitate tracking changes and observing both the global trend and local hotspots where objects converge or diverge. Existing methods, however, often obscure critical local hotspots by only considering the start and end positions of objects' trajectories. To address this gap, we propose RouteFlow, a trajectory-aware animated transition method that effectively balances the global trend and local hotspots while minimizing occlusion. RouteFlow is inspired by a real-world bus route analogy: objects are regarded as passengers traveling together, with local hotspots representing bus stops where these passengers get on and off. Based on this analogy, animation paths are generated like bus routes, with the object layout generated similarly to seat allocation according to their destinations. Compared with state-of-the-art methods, RouteFlow better facilitates identifying the global trend and locating local hotspots while performing comparably in tracking objects' movements.

Original languageEnglish
Title of host publicationCHI 2025 - Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400713941
DOIs
Publication statusPublished - 26 Apr 2025
Event2025 CHI Conference on Human Factors in Computing Systems, CHI 2025 - Yokohama, Japan
Duration: 26 Apr 20251 May 2025

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2025 CHI Conference on Human Factors in Computing Systems, CHI 2025
Country/TerritoryJapan
CityYokohama
Period26/04/251/05/25

Keywords

  • animation
  • edge bundling
  • trajectory data

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