Head, Gaze, or Finger? Comparing Object Selection Techniques in Augmented Reality for People with Low Vision

Jul 16, 2026

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Augmented reality (AR) enhances visual perception for people with low vision by overlaying multimodal information, and selection-based augmentation can reduce distraction while letting users choose what to augment. Yet limited evidence explains PLV ability and preferences for AR object selection under visual and gaze control challenges. A mixed-methods study with 20 PLV and 18 sighted controls evaluated head-, gaze-, and finger-based selection with dwell confirmation in sitting and walking scenarios. Gaze improved initial pointing speed when seated; head offered the most stable and least mentally demanding interaction, while central-loss participants preferred finger for perceived control.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages16

Reading Time40 min

Introduction

Research Questions and Study Design

Findings and Implications

Head, Gaze, or Finger? Comparing Object Selection Techniques in Augmented Reality for People with Low Vision Ruijia Chen University of Wisconsin-Madison Madison, Wisconsin, USA [ruijia.chen@wisc.edu](ruijia.chen@wisc.edu) Tianyi Zhang University of Wisconsin-Madison Madison, Wisconsin, USA[tzhang628@wisc.edu](tzhang628@wisc.edu) Sanbrita Mondal University of Wisconsin-Madison Madison, Wisconsin, USA[smondal4@wisc.edu](smondal4@wisc.edu) Yukang Yan University of Rochester Rochester, New York, USA [yukang.yan@rochester.edu](yukang.yan@rochester.edu) Yuhang Zhao University of Wisconsin-Madison Madison, Wisconsin, USA [yuhang.zhao@cs.wisc.edu](yuhang.zhao@cs.wisc.edu) arXiv :2607 .06778v 1 [ cs .HC] 7 Jul 2026 Figure 1: We investigated low-vision users’ performance and experience with head-, gaze-, and finger-based selection techniques in sitting and walking scenarios. Abstract Augmented reality (AR) can enhance visual perception for people with low vision (PLV) by overlaying multimodal information. Selection-based augmentation further allows users to flexibly choose and augment relevant information while reducing distraction and visual clutter. However, little is known about the ability and preferences of PLV in performing object selection techniques in AR, considering their potential visual and gaze control challenges. To understand what selection techniques are suitable for PLV to support selection-based AR augmentations, we conducted a mixedmethods study with 20 PLV and 18 sighted controls who performed target selection tasks using three input techniques—head, gaze, and finger pointing with dwell-based confirmation—in two realworld scenarios (sitting vs. on the go) . We found that for PLV, gaze-based selection enabled the fastest initial pointing when sitting and comparable overall selection time to head-based selection in both scenarios; however, due to reduced gaze stability, headbased selection remained the most stable and the least mentally demanding. Uniquely, participants with central vision loss preferred finger-based selection, reporting a greater sense of control. Our results provide empirical insights into accessible AR interaction techniques and selection-based vision enhancements for PLV. CCS Concepts • Human-centered computing → Accessibility design and evaluation methods; Mixed / augmented reality. Keywords Accessibility, Augmented Reality, Assistive Technologies, People with Low Vision, Selection Techniques 1 Introduction People with low vision (PLV) have functional vision but experience uncorrectable visual impairments, such as central or peripheral vision loss, blurred vision, and night blindness [67] . Augmented reality (AR) technology presents potential in enhancing PLV’s visual perception by overlaying multimodal information onto the physical world, such as highlighting a searched product in grocery shopping [103], distinguishing the graspable and non-graspable area of kitchen tools with AR overlays [49], generating virtual labels and signs to support indoor wayfinding [12, 31, 101], and augmenting stairs and outlining obstacles for safe navigation [25, 104] . However, existing AR systems often assume certain types of objects to augment, overlooking users’ agency in determining and selecting what they want to augment. Prior research has highlighted the importance of sense of autonomy in assistive technologies [29, 72] . To enhance user agency, it is critical to design selection-based augmentation systems and explore how to enable PLV to efficiently and easily select objects to augment in different scenarios. While various input techniques have been designed and evaluated in AR context, such as head-, gaze-, and finger-based selections [7, 8, 45, 52, 60], prior work only focuses on the performance and experiences of sighted users [16, 37, 76] . In contrast to sighted users, low-vision people face unique object selection challenges. For example, they may not be able t

FAQs

What selection techniques were compared for people with low vision in the study?

The study compared head-based, gaze-based, and finger-pointing selection techniques using dwell-based confirmation.

How did gaze-based selection perform for users in the sitting scenario?

For people with low vision, gaze-based selection enabled the fastest initial pointing in the sitting scenario.

Which technique was considered most stable and least mentally demanding, and why?

Head-based selection remained the most stable and least mentally demanding because maintaining gaze dwelling stability was more difficult for participants with low vision.

Jul 16, 2026

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