Exploring AR Label Placements in Visually Cluttered Scenarios

TL;DR

This paper explores new label placement methods in AR for cluttered scenes, demonstrating that spatial grouping of similar items improves user task performance in complex environments.

Contribution

It introduces and evaluates three label placement techniques tailored for cluttered AR scenes, emphasizing spatial grouping to enhance user understanding.

Findings

Spatial grouping of similar items aids in data identification.

Label placement improves task efficiency in cluttered environments.

Three techniques are compared for effectiveness in AR scenarios.

Abstract

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.