Reading Speed, Image Quality Ratings, and Comfort Ratings in Augmented Reality

2026-04-29

AI Summary

This study addresses the lack of a unified benchmark for objectively evaluating reading speed, image quality, and visual comfort in text rendering on current augmented reality (AR) head-mounted displays. To bridge this gap, the authors introduce the Read-AR dataset, which comprises over 11,000 reading speed measurements and nearly 6,000 subjective ratings collected under controlled experimental conditions across more than 80 distinct display configurations. This dataset enables the first large-scale, standardized assessment of AR reading experiences, facilitating objective, cross-device, and cross-parameter comparisons. By providing a reproducible and highly consistent reference, Read-AR supports rigorous performance evaluation and optimization of AR display systems.

Abstract

The rendering and display of text is a key use-case for augmented reality (AR). Here, we present the Read-AR, a dataset of reading in AR, for which we collected over 11,000 reading speeds and almost 6000 visual quality and comfort ratings across over 80 different experiment conditions on the same experiment set-up. The consistent, controlled set-up enables the dataset to function as a reference for benchmarking the quality of different AR headset architectures.

Problem

• Augmented Reality
• Reading Speed
• Image Quality
• Visual Comfort
• Text Rendering

Innovation

• Read-AR dataset
• reading speed
• visual quality
• comfort rating
• AR headset benchmarking