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.
翻译:尽管低视力人群可以通过屏幕放大镜读书,但阅读速度缓慢、体验欠佳。眼动追踪技术有望通过识别细粒度的注视行为并提供更有针对性的增强来改善其体验。为了激发基于注视行为的低视力技术,我们探究了通过商用眼动追踪仪收集低视力用户眼动数据的适当方法,并通过他们的眼动行为深入探讨了他们在阅读方面遇到的挑战。通过改进的校准界面,我们收集了20名低视力参与者和20名视力正常的对照者在计算机屏幕上进行阅读任务的注视数据;低视力参与者还被要求使用不同的屏幕放大镜进行阅读。我们发现,采用可访问的校准界面和数据收集方法,商用眼动追踪仪可以从低视力和视力正常的人身上获得可比较的注视数据。我们的研究确定了低视力人群在阅读过程中独特的视线模式,基于此,我们提出了针对基于注视行为的低视力技术的设计建议。