MultiMediate: Multi-modal Group Behaviour Analysis for Artificial Mediation

Which one is me? Identifying Oneself on Public Displays

Mohamed Khamis, Christian Becker, Andreas Bulling, Florian Alt

Proc. ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), pp. 287:1-287:12, 2018.

Best paper honourable mention award


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.



@inproceedings{khamis18_chi_2, title = {Which one is me? Identifying Oneself on Public Displays}, author = {Khamis, Mohamed and Becker, Christian and Bulling, Andreas and Alt, Florian}, year = {2018}, booktitle = {Proc. ACM SIGCHI Conference on Human Factors in Computing Systems (CHI)}, doi = {10.1145/3173574.3173861}, pages = {287:1-287:12}, video = {} }