GazeDrone: Mobile Eye-Based Interaction in Public Space Without Augmenting the User

Khamis, M. , Kienle, A., Alt, F. and Bulling, A. (2018) GazeDrone: Mobile Eye-Based Interaction in Public Space Without Augmenting the User. In: 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications (DroNet '18), Munich, Germany, 10-15 Jun 2018, pp. 66-71. ISBN 9781450358392 (doi: 10.1145/3213526.3213539)

Abstract

Gaze interaction holds a lot of promise for seamless human-computer interaction. At the same time, current wearable mobile eye trackers require user augmentation that negatively impacts natural user behavior while remote trackers require users to position themselves within a confined tracking range. We present GazeDrone, the first system that combines a camera-equipped aerial drone with a computational method to detect sidelong glances for spontaneous (calibration-free) gaze-based interaction with surrounding pervasive systems (e.g., public displays). GazeDrone does not require augmenting each user with on-body sensors and allows interaction from arbitrary positions, even while moving. We demonstrate that drone-supported gaze interaction is feasible and accurate for certain movement types. It is well-perceived by users, in particular while interacting from a fixed position as well as while moving orthogonally or diagonally to a display. We present design implications and discuss opportunities and challenges for drone-supported gaze interaction in public.

• Item Type: Conference Proceedings
• Additional Information: This work was funded, in part, by the Cluster of Excellence on Multimodal Computing and Interaction (MMCI) at Saarland University, Germany, and by the Bavarian State Ministry of Education, Science and the Arts in the framework of the Center Digitization.Bavaria (ZD.B). This research was supported by the German Research Foundation (DFG), Grant No. AL 1899/2-1.
• Keywords: Active eye tracking, drones, gaze interaction, UAV.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Khamis, Dr Mohamed
• Authors: Khamis, M., Kienle, A., Alt, F., and Bulling, A.
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: ACM
• ISBN: 9781450358392
• Copyright Holders: Copyright © 2018 The Authors
• First Published: First published in Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications: 66-71
• Publisher Policy: Reproduced in accordance with the publisher copyright policy