Reading Speed, Image Quality Ratings, and Comfort Ratings in Augmented Reality
Minjung Kim, Saeideh Ghahghaei Nezamabadi, Trisha Lian, Anand Singh

TL;DR
This paper introduces Read-AR, a comprehensive dataset of reading performance, visual quality, and comfort ratings in augmented reality, serving as a benchmark for AR headset evaluation.
Contribution
The creation of a large, controlled dataset of reading metrics and ratings in AR, enabling standardized benchmarking of AR headset architectures.
Findings
Over 11,000 reading speed measurements collected
Almost 6,000 visual quality and comfort ratings obtained
Dataset covers 80+ experiment conditions for benchmarking
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.
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