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Related Experiment Video

Updated: Oct 22, 2025

Photorealistic Learned Landscapes for Augmented Reality
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A Partially-Sorted Concentric Layout for Efficient Label Localization in Augmented Reality.

Zijing Zhou, Lili Wang, Voicu Popescu

    IEEE Transactions on Visualization and Computer Graphics
    |August 27, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel partially-sorted concentric label layout for augmented reality (AR) to improve label searching efficiency. The new AR labeling method significantly reduces search time compared to conventional layouts.

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    Area of Science:

    • Computer Science
    • Human-Computer Interaction
    • Augmented Reality

    Background:

    • Augmented reality (AR) labeling commonly uses flags attached to 3D anchor points.
    • High label density degrades interface efficiency due to sequential search.
    • Alphabetical sorting causes long, intersecting leader lines, complicating label identification.

    Purpose of the Study:

    • To develop an efficient AR labeling layout that balances search speed and visual clarity.
    • To mitigate issues of long and intersecting leader lines in dense AR environments.
    • To reduce label searching time in augmented reality interfaces.

    Main Methods:

    • Proposes a partially-sorted concentric label layout.
    • Labels are partitioned into sorted sequences on concentric circles of increasing radii.
    • Utilizes circular permutation theory to bound the number of circles required.

    Main Results:

    • The proposed layout effectively reduces label searching time.
    • A user study demonstrated significant time reduction compared to single-circle layouts.
    • The number of circles is limited, e.g., 12 labels require at most three circles.

    Conclusions:

    • Partially-sorted concentric layout improves AR label search efficiency.
    • This method avoids visual clutter from intersecting leader lines.
    • Offers a scalable solution for dense augmented reality labeling challenges.