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An augmented reality sign-reading assistant for users with reduced vision
Open accessAbstract
People typically rely heavily on visual information when finding their way to unfamiliar locations. For individuals with reduced vision, there are a variety of navigational tools available to assist with this task if needed. However, for wayfinding in unfamiliar indoor environments the applicability of existing tools is limited. One potential approach to assist with this task is to enhance visual information about the location and content of existing signage in the environment. With this aim, we developed a prototype software application, which runs on a consumer head-mounted augmented reality (AR) device, to assist visually impaired users with sign-reading. The sign-reading assistant identifies real-world text (e.g., signs and room numbers) on command, highlights the text location, converts it to high contrast AR lettering, and optionally reads the content aloud via text-to-speech. We assessed the usability of this application in a behavioral experiment. Participants with simulated visual impairment were asked to locate a particular office within a hallway, either with or without AR assistance (referred to as the AR group and control group, respectively). Subjective assessments indicated that participants in the AR group found the application helpful for this task, and an analysis of walking paths indicated that these participants took more direct routes compared to the control group. However, participants in the AR group also walked more slowly and took more time to complete the task than the control group. The results point to several specific future goals for usability and system performance in AR-based assistive tools.
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“It has been used for assistance during shopping [35], the climbing of stairs [33], and sign reading [11].”
From Pressing a Button You Cannot See: Evaluating Visual Designs to Assist Persons with Low Vision through Augmented Reality (2021) · cites this paper as [11]
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Metadata
- Authors
- Huang, J., Kinateder, M., Dunn, M. J., Jarosz, W., Yang, X.-D., & Cooper, E. A.
- Affiliations
- Dartmouth College (US)
- Cardiff University (GB)
- Corresponding author
- Huang, Jonathan
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2019-01-16
- Volume
- 14
- Issue
- 1
- Pages
- e0210630
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC6334915
- OpenAlex
- W2909795082
- Cited by
- 75
- References
- 25
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 9 · 2023: 8 · 2022: 9 · 2021: 16 · 2020: 11 · 2019: 4
- FWCI
- 4.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- NPARC (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Microsoft
- Oculus
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Keywords
- augmented reality, decreased vision, visual impairment, wayfinding, indoor navigation, head-mounted displays, text detection, text-to-speech, assistive technology, usability, route efficiency
- MeSH terms
- Virtual Reality, Female, Humans, Male, User-Computer Interface, Persons with Visual Disabilities, Visually Impaired Persons, Young Adult
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