@inproceedings{a19298b4e95249e1b7b5682f94683c03,
title = "Annotation Tool for Precise Emotion Ground Truth Label Acquisition while Watching 360° VR Videos",
abstract = "We demonstrate an HMD-based annotation tool for collecting precise emotion ground truth labels while users are watching 360° videos in Virtual Reality (VR). Our tool uses an HTC VIVE Pro Eye HMD for displaying 360° videos, a Joy-Con controller for inputting emotion annotations, and an Empatica E4 wristband for capturing physiological signals. Timestamps of these devices are synchronized via an NTP server. Following dimensional emotion models, users can report their emotion in terms of valence and arousal as they watch a video in VR. Annotation feedback is provided through two peripheral visualization techniques: HaloLight and DotSize. Our annotation tool provides a starting point for researchers to design momentary and continuous self-reports in virtual environments to enable fine-grained emotion recognition.",
keywords = "360°video, continuous, emotion annotation, ground truth labels",
author = "Tong Xue and Ali, {Abdallah El} and Gangyi Ding and Pablo Cesar",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 3rd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2020 ; Conference date: 14-12-2020 Through 18-12-2020",
year = "2020",
month = dec,
doi = "10.1109/AIVR50618.2020.00076",
language = "English",
series = "Proceedings - 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "371--372",
booktitle = "Proceedings - 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2020",
address = "United States",
}