Smooth Gaze: a framework for recovering tasks across devices using eye tracking

A user task is often distributed across devices, e.g., a student listening to a lecture in a classroom while watching slides on a projected screen and making notes on her laptop, and sometimes checking Twitter for comments on her smartphone. In scenarios like this, users move between heterogeneous devices and have to deal with task resumption overhead from both physical and mental perspectives. To address this problem, we created Smooth Gaze, a framework for recording the user’s work state and resuming it seamlessly across devices by leveraging implicit gaze input. In particular, we propose two novel and intuitive techniques, smart watching and smart posting, for detecting which display and target region the user is looking at, and transferring and integrating content across devices respectively. In addition, we designed and implemented a cross-device reading system SmoothReading that captures content from secondary devices and generates annotations based on eye tracking, to be displayed on the primary device. We conducted a study that showed that the system supported information seeking and task resumption, and improved users’ overall reading experience.