An end-to-end review of gaze estimation and its interactive applications on handheld mobile devices

Lei, Y., He, S., Khamis, M. and Ye, J. (2023) An end-to-end review of gaze estimation and its interactive applications on handheld mobile devices. ACM Computing Surveys, (doi: 10.1145/3606947) (Early Online Publication)

Abstract

In recent years we have witnessed an increasing number of interactive systems on handheld mobile devices which utilise gaze as a single or complementary interaction modality. This trend is driven by the enhanced computational power of these devices, higher resolution and capacity of their cameras, and improved gaze estimation accuracy obtained from advanced machine learning techniques, especially in deep learning. As the literature is fast progressing, there is a pressing need to review the state of the art, delineate the boundary, and identify the key research challenges and opportunities in gaze estimation and interaction. This paper aims to serve this purpose by presenting an end-to-end holistic view in this area, from gaze capturing sensors, to gaze estimation workflows, to deep learning techniques, and to gaze interactive applications.

• Item Type: Articles
• Status: Early Online Publication
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Khamis, Dr Mohamed
• Authors: Lei, Y., He, S., Khamis, M., and Ye, J.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: ACM Computing Surveys
• Publisher: Association for Computing Machinery (ACM)
• ISSN: 0360-0300
• ISSN (Online): 1557-7341
• Published Online: 30 June 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in ACM Computing Surveys 2023
• Publisher Policy: Reproduced in accordance with the publisher copyright policy