GazeProjector: Accurate Gaze Estimation and Seamless Gaze Interaction Across Multiple Displays

Mobile gaze-based interaction with multiple displays may occur from arbitrary positions and orientations. However, maintaining high gaze estimation accuracy in such situa-tions remains a significant challenge. In this paper, we present GazeProjector, a system that combines (1) natural feature tracking on displays to determine the mobile eye tracker's position relative to a display with (2) accurate point-of-gaze estimation. GazeProjector allows for seam-less gaze estimation and interaction on multiple displays of arbitrary sizes independently of the user's position and orientation to the display. In a user study with 12 partici-pants we compare GazeProjector to established methods (here: visual on-screen markers and a state-of-the-art video-based motion capture system). We show that our approach is robust to varying head poses, orientations, and distances to the display, while still providing high gaze estimation accuracy across multiple displays without re-calibration for each variation. Our system represents an important step towards the vision of pervasive gaze-based interfaces.