Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges

Object recognition technologies hold the potential to support blind and low-vision people in navigating the world around them. However, the gap between benchmark performances and practical usability remains a signifcant challenge. This paper presents a study aimed at understanding blind users' interaction with object recognition systems for identifying and avoiding errors. Leveraging a pre-existing object recognition system, URCam, fne-tuned for our experiment, we conducted a user study involving 12 blind and low-vision participants. Through in-depth interviews and hands-on error identifcation tasks, we gained insights into users' experiences, challenges, and strategies for identifying errors in camera-based assistive technologies and object recognition systems. During interviews, many participants preferred independent error review, while expressing apprehension toward misrecognitions. In the error identifcation task, participants varied viewpoints, backgrounds, and object sizes in their images to avoid and overcome errors. Even after repeating the task, participants identifed only half of the errors, and the proportion of errors identifed did not signifcantly difer from their frst attempts. Based on these insights, we ofer implications for designing accessible interfaces tailored to the needs of blind and low-vision users in identifying object recognition errors.