Whatever could be, could be: Visualizing Future Movement Predictions
Chenkai Zhang, Ruochen Cao, Andrew Cunningham, James A. Walsh · 2024
As technology grants us superhuman powers, looking into what the future may hold is no longer science fiction. Artificial Intelligence and Mixed Reality technologies can allow users to see what the future may hold. In this paper, we present our work evaluating visualizations of future predictions in the Football domain. We explore the problem space, examining what a future may be. Three visualizations—2 Arrow Lines, 5 Arrow Lines, and Heatmap—are introduced as representations that show both individual predictions of movement (2 Arrow Lines and 5 Arrow Lines) and more generalized predictions (Heatmap). Whilst football is used as an example domain in this work, the visualizations and findings aim to generalize to other scenarios that contain trajectory information. Two VR studies $(2 \times \mathrm{n}=24)$ examined the visualizations in both simple/complex, timed/non-timed, and short/long-range viewing situations. Results show Heatmap as the most effective and preferred by the vast majority of participants. Findings offer insights into future visualization, serving as visual heuristics beyond the realm of sports and into the real world.