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Main Authors: Park, Ji Hwan, Roper, Braden, Arezoumand, Amirhossein, Tran, Tien
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.00198
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author Park, Ji Hwan
Roper, Braden
Arezoumand, Amirhossein
Tran, Tien
author_facet Park, Ji Hwan
Roper, Braden
Arezoumand, Amirhossein
Tran, Tien
contents We investigate methods for placing labels in AR environments that have visually cluttered scenes. As the number of items increases in a scene within the user' FOV, it is challenging to effectively place labels based on existing label placement guidelines. To address this issue, we implemented three label placement techniques for in-view objects for AR applications. We specifically target a scenario, where various items of different types are scattered within the user's field of view, and multiple items of the same type are situated close together. We evaluate three placement techniques for three target tasks. Our study shows that using a label to spatially group the same types of items is beneficial for identifying, comparing, and summarizing data.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00198
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Exploring AR Label Placements in Visually Cluttered Scenarios
Park, Ji Hwan
Roper, Braden
Arezoumand, Amirhossein
Tran, Tien
Human-Computer Interaction
We investigate methods for placing labels in AR environments that have visually cluttered scenes. As the number of items increases in a scene within the user' FOV, it is challenging to effectively place labels based on existing label placement guidelines. To address this issue, we implemented three label placement techniques for in-view objects for AR applications. We specifically target a scenario, where various items of different types are scattered within the user's field of view, and multiple items of the same type are situated close together. We evaluate three placement techniques for three target tasks. Our study shows that using a label to spatially group the same types of items is beneficial for identifying, comparing, and summarizing data.
title Exploring AR Label Placements in Visually Cluttered Scenarios
topic Human-Computer Interaction
url https://arxiv.org/abs/2507.00198