OptWedge: Cognitive Optimized Guidance toward Off-screen POIs

TL;DR

OptWedge introduces a cognitively optimized visual guidance method for off-screen POIs, improving localization accuracy over traditional heuristics by considering cognitive costs and individual differences.

Contribution

The paper proposes OptWedge, a novel optimization approach for off-screen POI guidance that accounts for cognitive factors, enhancing accuracy over existing methods.

Findings

OptWedge outperforms heuristics in close-distance guidance accuracy.

Unbiased and biased variants of OptWedge show different performance benefits.

Cognitive cost optimization improves off-screen POI localization.

Abstract

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.