Abstract
Gaze is a powerful measure of people’s attracted attention and reveals where we are looking at within our current field of view. 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.
Original language | English |
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Title of host publication | Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia (MUM 2017) |
Publisher | Association for Computing Machinery |
Publication date | 2017 |
Pages | 279-291 |
ISBN (Print) | 978-1-4503-5378-6 |
DOIs | |
Publication status | Published - 2017 |
Event | 16th International Conference on Mobile and Ubiquitous Multimedia - Stuttgart, Germany Duration: 26 Nov 2017 → 29 Nov 2017 |
Conference
Conference | 16th International Conference on Mobile and Ubiquitous Multimedia |
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Country/Territory | Germany |
City | Stuttgart |
Period | 26/11/2017 → 29/11/2017 |