Eyemirror: mobile calibration-free gaze approximation using corneal imaging

Christian Lander; Sven Gehring; Markus Löchtefeld; Andreas Bulling; Antonio Krüger

In: Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia. International Conference on Mobile and Ubiquitous Multimedia (MUM-2017), 16th, November 26-29, Stuttgart, Germany, ISBN 978-1-4503-5378-6, ACM, 11/2017.


Gaze is a powerful measure of people's attracted attention and reveals where we are looking within our current FOV. Hence gaze-based interfaces are gaining in importance. However, gaze estimation usually requires extensive hardware and depends on a calibration that has to be renewed regularly. We present EyeMirror, a mobile device for calibration-free gaze approximation on surfaces (e.g., displays). It consists of a head-mounted camera, connected to a wearable mini-computer, capturing the environment reflected on the human cornea. The corneal images are analyzed using natural feature tracking for gaze estimation on surfaces. In two lab studies we compared variations of EyeMirror against established methods for gaze estimation in a display scenario, and investigated the effect of display content (i.e. number of features). EyeMirror achieved 4.03° gaze estimation error, while we found no significant effect of display content.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence