EyeInfo Research Group

Paper published in the Proceedings of the 2012 Symposium on Eye Tracking Research & Applications (ETRA 2012)
Location: Santa Barbara, CA, USA
Date: Mar, 2012
Publisher: ACM
ISBN/ISSN: 978-1-4503-1221-9
Pages: 139-146
DOI Bookmark: 10.1145/2168556.2168578

Authors:
Diako Mardanbegi, IT University of Copenhagen
Dan Witzner Hansen, IT University of Copenhagen
Thomas Pederson, IT University of Copenhagen

Abstract:
A novel method for video-based head gesture recognition using eye information by an eye tracker has been proposed. The method uses a combination of gaze and eye movement to infer head gestures. Compared to other gesture-based methods a major advantage of the method is that the user keeps the gaze on the interaction object while interacting. This method has been implemented on a head-mounted eye tracker for detecting a set of predefined head gestures. The accuracy of the gesture classifier is evaluated and verified for gaze-based interaction in applications intended for both large public displays and small mobile phone screens. The user study shows that the method detects a set of defined gestures reliably.

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