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.
@article{arxiv.2502.08076,
title = {RouteFlow: Trajectory-Aware Animated Transitions},
author = {Duan Li and Xinyuan Guo and Xinhuan Shu and Lanxi Xiao and Lingyun Yu and Shixia Liu},
journal= {arXiv preprint arXiv:2502.08076},
year = {2025}
}