Even before the Covid-19 pandemic, beneficial use cases for hygienic, touchless human-machine interaction have been explored. Gaze input, i.e., information input via eye-movements of users, represents a promising method for contact-free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webcam, available on most of today's laptops, and only requires a one-point calibration before use. GaVe is designed in a hierarchical structure, presenting broad item cluster to users first and subsequently guiding them through another selection round, which allows the presentation of a large number of items. Cluster/item selection in GaVe is based on the dwell time of fixations, i.e., the time duration that users look at a given Cluster/item. A user study (N=22) was conducted to test optimal dwell time thresholds and comfortable human-to-display distances. Users' perception of the system, as well as error rates and task completion time were registered. We found that all participants were able to use the system with a short time training, and showed good performance during system usage, selecting a target item within a group of 12 items in 6.76 seconds on average. Participants were able to quickly understand and know how to interact with the interface. We provide design guidelines for GaVe and discuss the potentials of the system.

翻译：即使在新冠疫情之前，人们已开始探索卫生、非接触式人机交互的有益用例。基于用户眼球运动的信息输入——注视输入，是人机系统中实现无接触交互的一种有前景的方法。本文提出"凝视自动售货接口"(GaVe)，允许用户通过眼睛控制显示屏上的操作。该接口使用当今大多数笔记本电脑配备的普通网络摄像头，使用时仅需一次单点标定。GaVe采用分层结构设计：首先向用户展示较大类别的项目集群，然后引导用户进入下一轮选择，从而支持大量项目的呈现。集群/项目选择基于注视停留时间，即用户注视特定集群/项目的持续时间。我们通过一项包含22名用户的实验，测试了最优停留时间阈值及舒适的人-显示器距离，并记录了用户对系统的感知、错误率及任务完成时间。研究发现，所有参与者经过短期训练即可使用该系统，且在使用过程中表现良好——在12个项目中平均用时6.76秒完成目标选择。参与者能快速理解接口交互方式。我们提供了GaVe的设计指南，并讨论了该系统的应用潜力。