Review: Experimental Evaluation of User Interfaces for Visual Indoor Navigation

This paper presents methods for indoor mobile localization, using AR and VR techniques. Specifically, it explores & describes a "novel" UI implementation which consists of Virtual Reality and Augmented Reality views that "ensure localization accuracy", in situations such as a person being in an airport and the phone gives directions. The technology uses computer vision to capture and match images of the environment with previously recorded reference images of known location. The problem, however, lies in building an UI which addresses the issue of "visual localization", which the paper describes and showcases with the help of a working prototype and a series of experiments.

In terms of content, the paper discusses previous work done in the field and also the related background. In this section, the authors argue why "visual localization" is better than other techniques available. The reader is also introduced to the Augmented Reality and Virtual Reality concepts, in the context of UI's for pedestrian navigation systems.

Before building a prototype, the authors conducted an experiment on users to understand the user preference in terms of AR vs VR. In order to confirm the hypotheses, the authors built a mobile app and performed 3 experiments, one per hypothesis. Following the experiments, they were able to confirm the hypotheses and draw the conclusions. In the final section, they discuss how AR can be improved, limitations of the technique, and also how future work could combine AR and VR to provide better UI's.

Overall, the paper is very good, with the minor flaw that it sometimes talks about a certain concept without providing a reference to it. In terms of influence, the paper is cited only twice in reports done by university students, and in one of them it is argued that the general method employed in this paper are usually not reliable.

Citation:

CHI '14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 3607-3616 ACM New York, NY, USA ©2014

Paper link: http://dl.acm.org/citation.cfm?id=2557003