Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2025

Abstract

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The results showed that all participants could run at least 1km (mean = 3.44 km) using RunSight, while none could engage in Caller-style guided running without it. Our participants could run safely because they effectively synthesized RunSight-provided cues and information gained from runner-guide communication.

Keywords

accessibility, augmented reality, low-vision individuals, guided run-ning, nighttime outdoor exercise

Discipline

Graphics and Human Computer Interfaces | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Areas of Excellence

Digital transformation

Publication

CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, April 26 - May 1

First Page

1

Last Page

20

Identifier

10.1145/3706598.3714284

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3706598.3714284

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