  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 significant 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, fine-tuned for our experiment,
we conducted a user study involving 12 blind and low-vision participants.
Through in-depth interviews and hands-on error identification 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 identification
task, participants varied viewpoints, backgrounds, and object sizes in their
images to avoid and overcome errors. Even after repeating the task,
participants identified only half of the errors, and the proportion of errors
identified did not significantly differ from their first attempts. Based on
these insights, we offer implications for designing accessible interfaces
tailored to the needs of blind and low-vision users in identifying object
recognition errors.
