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Main Authors: Ren, Yutong, Reddy, Arnav, Nebeling, Michael
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.18350
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author Ren, Yutong
Reddy, Arnav
Nebeling, Michael
author_facet Ren, Yutong
Reddy, Arnav
Nebeling, Michael
contents Gaze-based selection in XR requires visual confirmation due to eye-tracking limitations and target ambiguity in 3D contexts. Current designs for wide-FOV displays use world-locked, central overlays, which are not conducive to always-on AR glasses. This paper introduces PeriphAR (per-ree-far), a visualization technique that leverages peripheral vision for feedback during gaze-based selection on a monocular AR display. In a first user study, we isolated text, color, and shape properties of target objects to compare peripheral selection cues. Peripheral vision was more sensitive to color than shape, but this sensitivity rapidly declined at lower contrast. To preserve preattentive processing of color, we developed two strategies to enhance color in users' peripheral vision. In a second user study, our strategy that maximized contrast of the target to the neighboring object with the most similar color was subjectively preferred. As proof of concept, we implemented PeriphAR in an end-to-end system to test performance with real-world object detection.
format Preprint
id arxiv_https___arxiv_org_abs_2603_18350
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle PeriphAR: Fast and Accurate Real-World Object Selection with Peripheral Augmented Reality Displays
Ren, Yutong
Reddy, Arnav
Nebeling, Michael
Human-Computer Interaction
Gaze-based selection in XR requires visual confirmation due to eye-tracking limitations and target ambiguity in 3D contexts. Current designs for wide-FOV displays use world-locked, central overlays, which are not conducive to always-on AR glasses. This paper introduces PeriphAR (per-ree-far), a visualization technique that leverages peripheral vision for feedback during gaze-based selection on a monocular AR display. In a first user study, we isolated text, color, and shape properties of target objects to compare peripheral selection cues. Peripheral vision was more sensitive to color than shape, but this sensitivity rapidly declined at lower contrast. To preserve preattentive processing of color, we developed two strategies to enhance color in users' peripheral vision. In a second user study, our strategy that maximized contrast of the target to the neighboring object with the most similar color was subjectively preferred. As proof of concept, we implemented PeriphAR in an end-to-end system to test performance with real-world object detection.
title PeriphAR: Fast and Accurate Real-World Object Selection with Peripheral Augmented Reality Displays
topic Human-Computer Interaction
url https://arxiv.org/abs/2603.18350