Understanding How Low Vision People Read Using Eye Tracking
Ru Wang, Linxiu Zeng, Xinyong Zhang, Sanbrita Mondal, Yuhang Zhao
摘要
While being able to read with screen magnifiers, low vision people have slow and unpleasant reading experiences. Eye tracking has the potential to improve their experience by recognizing fine-grained gaze behaviors and providing more targeted enhancements. To inspire gaze-based low vision technology, we investigate the suitable method to collect low vision users’ gaze data via commercial eye trackers and thoroughly explore their challenges in reading based on their gaze behaviors. With an improved calibration interface, we collected the gaze data of 20 low vision participants and 20 sighted controls who performed reading tasks on a computer screen; low vision participants were also asked to read with different screen magnifiers. We found that, with an accessible calibration interface and data collection method, commercial eye trackers can collect gaze data of comparable quality from low vision and sighted people. Our study identified low vision people’s unique gaze patterns during reading, building upon which, we propose design implications for gaze-based low vision technology.
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- GazePrompt: Enhancing Low Vision People's Reading Experience with Gaze-Aware AugmentationsRu Wang, Zach Potter, Yun Ho, Daniel Killough 等CHI 2024 · 被引用 13 次
- Towards Enhancing Low Vision Usability of Data Charts on SmartphonesYash Prakash, Pathan Aseef Khan, Akshay Kolgar Nayak, Sampath Jayarathna 等IEEE VIS 2024 · 被引用 6 次
- Improving Low-Vision Chart Accessibility via On-Cursor Visual ContextYotam Sechayk, Hennes Rave, Max Rädler, Mark Colley 等CHI 2026 · 被引用 1 次
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