@inproceedings{84adafe7950149aa8dc4cc9d66cab0d2,
title = "Investigating the Relationship between Momentary Emotion Self-reports and Head and Eye Movements in HMD-based 360 VR Video Watching",
abstract = "Inferring emotions from Head Movement (HM) and Eye Movement (EM) data in 360 Virtual Reality (VR) can enable a low-cost means of improving users' Quality of Experience. Correlations have been shown between retrospective emotions and HM, as well as EM when tested with static 360 images. In this early work, we investigate the relationship between momentary emotion self-reports and HM/EM in HMD-based 360 VR video watching. We draw on HM/EM data from a controlled study (N=32) where participants watched eight 1-minute 360 emotion-inducing video clips, and annotated their valence and arousal levels continuously in real-time. We analyzed HM/EM features across fine-grained emotion labels from video segments with varying lengths (5-60s), and found significant correlations between HM rotation data, as well as some EM features, with valence and arousal ratings. We show that fine-grained emotion labels provide greater insight into how HM/EM relate to emotions during HMD-based 360 VR video watching.",
keywords = "360 video, Emotion, eye movement, head movement, virtual reality",
author = "Tong Xue and Ali, {Abdallah El} and Gangyi Ding and Pablo Cesar",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI EA 2021 ; Conference date: 08-05-2021 Through 13-05-2021",
year = "2021",
month = may,
day = "8",
doi = "10.1145/3411763.3451627",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA 2021",
}