The Eye in Extended Reality: A Survey on Gaze Interaction and Eye Tracking in Head-worn Extended Reality-Reference-Cited by-同舟云学术

The Eye in Extended Reality: A Survey on Gaze Interaction and Eye Tracking in Head-worn Extended Reality

Published:2022-03-25 Issue:3 Volume:55 Page:1-39
ISSN:0360-0300
Container-title:ACM Computing Surveys
language:en
Short-container-title:ACM Comput. Surv.

Author:

Plopski Alexander¹^ORCID,Hirzle Teresa²^ORCID,Norouzi Nahal³^ORCID,Qian Long⁴^ORCID,Bruder Gerd⁵^ORCID,Langlotz Tobias¹^ORCID

Affiliation:

1. Department of Information Science, University of Otago, Dunedin, New Zealand

2. Institute of Media Informatics, Ulm University, Ulm, Germany

3. College of Engineering and Computer Science, University of Central Florida, Orlando, FL

4. Department of Computer Science, Johns Hopkins University, Baltimore, MD

5. Institute for Simulation and Training, University of Central Florida, Orlando, FL

Abstract

With innovations in the field of gaze and eye tracking, a new concentration of research in the area of gaze-tracked systems and user interfaces has formed in the field of Extended Reality (XR). Eye trackers are being used to explore novel forms of spatial human–computer interaction, to understand human attention and behavior, and to test expectations and human responses. In this article, we review gaze interaction and eye tracking research related to XR that has been published since 1985, which includes a total of 215 publications. We outline efforts to apply eye gaze for direct interaction with virtual content and design of attentive interfaces that adapt the presented content based on eye gaze behavior and discuss how eye gaze has been utilized to improve collaboration in XR. We outline trends and novel directions and discuss representative high-impact papers in detail.

Funder

National Science Foundation

Office of Naval Research

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Link

https://dl.acm.org/doi/pdf/10.1145/3491207

Reference274 articles.

1. Scene understanding — A survey

2. Toward Real-Time System Adaptation Using Excitement Detection from Eye Tracking