Which One is Me?: Identifying Oneself on Public Displays

Khamis, M. , Becker, C., Bulling, A. and Alt, F. (2018) Which One is Me?: Identifying Oneself on Public Displays. In: 2018 CHI Conference on Human Factors in Computing Systems, Montréal, QC, Canada, 21-26 Apr 2018, p. 287. ISBN 9781450356206 (doi: 10.1145/3173574.3173861)

Abstract

While user representations are extensively used on public displays, it remains unclear how well users can recognize their own representation among those of surrounding users. We study the most widely used representations: abstract objects, skeletons, silhouettes and mirrors. In a prestudy (N=12), we identify five strategies that users follow to recognize themselves on public displays. In a second study (N=19), we quantify the users' recognition time and accuracy with respect to each representation type. Our findings suggest that there is a significant effect of (1) the representation type, (2) the strategies performed by users, and (3) the combination of both on recognition time and accuracy. We discuss the suitability of each representation for different settings and provide specific recommendations as to how user representations should be applied in multi-user scenarios. These recommendations guide practitioners and researchers in selecting the representation that optimizes the most for the deployment's requirements, and for the user strategies that are feasible in that environment.

• 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: Multiple users, public displays, user representations.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Khamis, Dr Mohamed
• Authors: Khamis, M., Becker, C., Bulling, A., and Alt, F.
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: ACM
• ISBN: 9781450356206
• Copyright Holders: Copyright © 2018 The Authors
• First Published: First published in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: 287
• Publisher Policy: Reproduced in accordance with the publisher copyright policy