English

OptWedge: Cognitive Optimized Guidance toward Off-screen POIs

Human-Computer Interaction 2022-06-10 v1 Machine Learning Neurons and Cognition

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.

Keywords

Cite

@article{arxiv.2206.04293,
  title  = {OptWedge: Cognitive Optimized Guidance toward Off-screen POIs},
  author = {Shoki Miyagawa},
  journal= {arXiv preprint arXiv:2206.04293},
  year   = {2022}
}

Comments

14 pages,7 figures, accepted to PDPTA 2021

R2 v1 2026-06-24T11:44:31.825Z