ArticleASSETS. Annual ACM Conference on Assistive Technologies2022
Blind Users Accessing Their Training Images in Teachable Object Recognizers.
Article in ASSETS. Annual ACM Conference on Assistive Technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Enabling Older Adults to Provide High-quality Activity Labels: Unpacking Accuracy, Precision, and Granularity in Activity Labeling.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025Article
- Human-AI Collaboration for Remote Sighted Assistance: Perspectives from the LLM Era.Future internet · 2024Article
- Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges.ASSETS. Annual ACM Conference on Assistive Technologies · 2024Article
- AccessShare: Co-designing Data Access and Sharing with Blind People.ASSETS. Annual ACM Conference on Assistive Technologies · 2024Article
- Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2023Article
- Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models.Proceedings of the SIGCHI conference on human factors in computing systems. CHI ConferenceArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Teachable object recognizers provide a solution for a very practical need for blind people - instance level object recognition. They assume one can visually inspect the photos they provide for training, a critical and inaccessible step for those who are blind. In this work, we engineer data descriptors that address this challenge. They indicate in real time whether the object in the photo is cropped or too small, a hand is included, the photos is blurred, and how much photos vary from each other. Our descriptors are built into open source testbed iOS app, called MYCam. In a remote user study in (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.