Abstract: The eyes are a particularly interesting modality for cognitive industrial assistance systems, as gaze analysis can reveal cognition- and task-related aspects, while gaze interaction depicts a lightweight and fast method for hands-free machine control. In this paper, we present mobEYEle, a body-worn eye tracking platform that performs the entire computation directly on the user, as opposed to primarily streaming the data to a centralized unit for online processing and hence restricting its pervasiveness. The applicability of the platform is demonstrated throughout extensive performance and battery runtime tests. Moreover, a self-contained calibration method is outlined that enables the usage of mobEYEle without any supervisor nor digital screen.
mobEYEle: An Embedded Eye Tracking Platform for Industrial Assistance
Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 International Symposium on Wearable Computers (UbiComp/ISWC ’19 Adjunct), Editors: Harle, Farrahi, Lane, 7 pages, DOI: 10.1145/3341162.3350842, September 2019.