ImageAssist: Tools for Enhancing Touchscreen-Based Image Exploration Systems for Blind and Low Vision Users
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Abstract (arXiv)
Blind and low vision (BLV) users often rely on alt text to understand what a digital image is showing. However, recent research has investigated how touch-based image exploration on touchscreens can supplement alt text. Touchscreen-based image exploration systems allow BLV users to deeply understand images while granting a strong sense of agency. Yet, prior work has found that these systems require a lot of effort to use, and little work has been done to explore these systems' bottlenecks on a deeper level and propose solutions to these issues. To address this, we present ImageAssist, a set of three tools that assist BLV users through the process of exploring images by touch -- scaffolding the exploration process. We perform a series of studies with BLV users to design and evaluate ImageAssist, and our findings reveal several implications for image exploration tools for BLV users.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Feb 2023.
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Citing papers per year: 2024: 3; 2025: 2; 2026: 1.
6 papers.
- 2024Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision Peoplecited by 24
- 2025Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptionscited by 6
- 2024SPIN: Hierarchical Segmentation with Subpart Granularity in Natural Imagescited by 5
- 2024Engaging with Children's Artwork in Mixed Visual-Ability Familiescited by 3
- 2026How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision Peoplecited by 3
- 2025SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answeringcited by 0
- 2026How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People13 Feb 2026
- 2025SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answering18 Nov 2025
- 2025Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions21 Jul 2025
- 2024Engaging with Children's Artwork in Mixed Visual-Ability Families26 Jul 2024
- 2024SPIN: Hierarchical Segmentation with Subpart Granularity in Natural Images12 Jul 2024
- 2024Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People22 Mar 2024