NDLI: Gaze-Based Interaction Intention Recognition in Virtual Reality

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Gaze-Based Interaction Intention Recognition in Virtual Reality

Content Provider	MDPI
Author	Chen, Xiao-Lin Hou, Wen-Jun
Copyright Year	2022
Description	With the increasing need for eye tracking in head-mounted virtual reality displays, the gaze-based modality has the potential to predict user intention and unlock intuitive new interaction schemes. In the present work, we explore whether gaze-based data and hand-eye coordination data can predict a user’s interaction intention with the digital world, which could be used to develop predictive interfaces. We validate it on the eye-tracking data collected from 10 participants in item selection and teleporting tasks in virtual reality. We demonstrate successful prediction of the onset of item selection and teleporting with an 0.943 $F1$ -Score using a Gradient Boosting Decision Tree, which is the best among the four classifiers compared, while the model size of the Support Vector Machine is the smallest. It is also proven that hand-eye-coordination-related features can improve interaction intention recognition in virtual reality environments.
Starting Page	1647
e-ISSN	20799292
DOI	10.3390/electronics11101647
Journal	Electronics
Issue Number	10
Volume Number	11
Language	English
Publisher	MDPI
Publisher Date	2022-05-21
Access Restriction	Open
Subject Keyword	Electronics Information and Library Science Intention Prediction Virtual Reality Gaze-based Interaction
Content Type	Text
Resource Type	Article

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