On the Applicability of Computer Vision based Gaze Tracking in Mobile Scenarios

Abstract

Gaze tracking is a common technique to study user interaction but is also increasingly used as input modality. In this regard, computer vision based systems provide a promising low-cost realization of gaze tracking on mobile devices. This paper complements related work focusing on algorithmic designs by conducting two users studies aiming to i) independently evaluate EyeTab as promising gaze tracking approach and ii) by providing the first independent use case driven evaluation of its applicability in mobile scenarios. Our evaluation elucidates the current state of mobile computer vision based gaze tracking and aims to pave the way for improved algorithms. In this regard, we aim to further foster the development by releasing our source data as reference database open to the public.