A study on attention guidance in AR for target localization
Abstract:
This work presents a design framework for AR attention-guiding cues in target localization tasks. Localization tasks involve identifying a target, moving toward it, and monitoring changes in the surrounding environment. Maintaining awareness of target-related information is challenging in real-world settings, where clutter, occlusion, and competing perceptual demands are present. AR provides a suitable environment for attention guidance because virtual cues can align with real-world targets and use sensory channels appropriate for the task and context. To understand how attention-guidance cues should express target-related information and remain noticeable in real-world localization settings, we conducted an ideation workshop with experts and novice users. Integrating perceptual and attentional perspectives, we analyzed ideas from the workshop and derived a design framework that structures attention-guidance cue design through four dimensions: What, How, Where, and When. We illustrate the framework through representative localization scenarios, including target finding, route following, and progress tracking. We conducted a two-stage evaluation to examine how well the framework supports real-world design and whether cues created with it help users perform localization tasks effectively.
Main reference:
Xie, L. Jiang, S. Xie, Q. Liu, H.-N. Liang, and L. Yu. “A study on attention guidance in AR for target localization.” In: Visual Informatics (2026), p. 100309. issn: 2468-502X. doi: https://doi.org/10.1016/j.visinf.2026.100309.
BibTeX:
@article{Xie:2026:ASA,
title = {A study on attention guidance in AR for target localization},
journal = {Visual Informatics},
volume = {10},
number = {3},
pages = {100309},
year = {2026},
issn = {2468-502X},
doi = {https://doi.org/10.1016/j.visinf.2026.100309},
url = {https://www.sciencedirect.com/science/article/pii/S2468502X26000057},
author = {Fuqi Xie and Luyan Jiang and Siqi Xie and Qianru Liu and Hai-Ning Liang and Lingyun Yu},
keywords = {Attention guidance, Visual cues, Auditory cues, Haptic cues, Augmented reality}}