Who is Alyx? A new behavioral biometric dataset for user identification in XR

IF 3.2 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Frontiers in virtual reality Pub Date : 2023-11-10 DOI:10.3389/frvir.2023.1272234
Rack, Christian, Fernando, Tamara, Yalcin, Murat, Hotho, Andreas, Latoschik, Marc Erich
{"title":"Who is Alyx? A new behavioral biometric dataset for user identification in XR","authors":"Rack, Christian, Fernando, Tamara, Yalcin, Murat, Hotho, Andreas, Latoschik, Marc Erich","doi":"10.3389/frvir.2023.1272234","DOIUrl":null,"url":null,"abstract":"This article presents a new dataset containing motion and physiological data of users playing the game \"Half-Life: Alyx\". The dataset specifically targets behavioral and biometric identification of XR users. It includes motion and eye-tracking data captured by a HTC Vive Pro of 71 users playing the game on two separate days for 45 minutes. Additionally, we collected physiological data from 31 of these users. We provide benchmark performances for the task of motion-based identification of XR users with two prominent state-of-the-art deep learning architectures (GRU and CNN). After training on the first session of each user, the best model can identify the 71 users in the second session with a mean accuracy of 95% within 2 minutes. The dataset is freely available under https://github.com/cschell/who-is-alyx","PeriodicalId":73116,"journal":{"name":"Frontiers in virtual reality","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in virtual reality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frvir.2023.1272234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

This article presents a new dataset containing motion and physiological data of users playing the game "Half-Life: Alyx". The dataset specifically targets behavioral and biometric identification of XR users. It includes motion and eye-tracking data captured by a HTC Vive Pro of 71 users playing the game on two separate days for 45 minutes. Additionally, we collected physiological data from 31 of these users. We provide benchmark performances for the task of motion-based identification of XR users with two prominent state-of-the-art deep learning architectures (GRU and CNN). After training on the first session of each user, the best model can identify the 71 users in the second session with a mean accuracy of 95% within 2 minutes. The dataset is freely available under https://github.com/cschell/who-is-alyx
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
谁是艾丽克斯?一种新的XR用户识别行为生物特征数据集
本文介绍了一个新的数据集,其中包含了玩游戏“半条命:Alyx”的用户的运动和生理数据。该数据集专门针对XR用户的行为和生物特征识别。它包括由HTC Vive Pro捕捉的动作和眼球追踪数据,71名用户分别在两天内玩了45分钟的游戏。此外,我们还收集了其中31名用户的生理数据。我们为基于动作的XR用户识别任务提供了两个突出的最先进的深度学习架构(GRU和CNN)的基准性能。在对每个用户的第一个会话进行训练后,最佳模型可以在2分钟内识别出第二个会话的71个用户,平均准确率为95%。该数据集可在https://github.com/cschell/who-is-alyx免费获得
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
5.80
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊最新文献
Experiential disparities in social VR: uncovering power dynamics and inequality Predictive multiuser redirected walking using artificial potential fields Synergy and medial effects of multimodal cueing with auditory and electrostatic force stimuli on visual field guidance in 360° VR Virtual reality training for intraoperative imaging in orthopaedic surgery: an overview of current progress and future direction Editorial: Virtual agents in virtual reality: design and implications for VR users
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1