OptWedge: Cognitive Optimized Guidance toward Off-screen POIs
This work addresses a domain-specific problem for users of smart devices and head-mounted displays, offering an incremental improvement over existing methods.
The paper tackled the problem of guiding users to off-screen points of interest on small-screen devices by optimizing a wedge figure to reduce cognitive bias and individual differences, resulting in more accurate guidance for close distances compared to heuristic methods.
Guiding off-screen points of interest (POIs) is a practical way of providing additional information to users of small-screen devices, such as smart devices and head-mounted displays. Popular previous methods involve displaying a primitive figure referred to as Wedge on the screen for users to estimate off-screen POI on the invisible vertex. Because they utilize a cognitive process referred to as amodal completion, where users can imagine the entire figure even when a part of it is occluded, localization accuracy is influenced by bias and individual differences. To improve the accuracy, we propose to optimize the figure using a cognitive cost that considers the influence. We also design two types of optimizations with different parameters: unbiased OptWedge (UOW) and biased OptWedge (BOW). Experimental results indicate that OptWedge achieves more accurate guidance for a close distance compared to heuristics approach.