arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2006.15432cs.HCcs.GRcs.LG
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Automatic Recommendation of Strategies for Minimizing Discomfort in Virtual Environments

Universidade Federal Fluminense(弗鲁米嫩塞联邦大学);Universidade Tecnologica Federal do Paraná(巴拉那联邦理工大学);Instituto Federal do Triangulo Mineiro(米纳斯三角洲联邦学院)

Thiago Porcino, Esteban Clua, Daniela Trevisan, Érick Rodrigues, Alexandre Silva

英文摘要:

Virtual reality (VR) is an imminent trend in games, education, entertainment, military, and health applications, as the use of head-mounted displays is becoming accessible to the mass market. Virtual reality provides immersive experiences but still does not offer an entirely perfect situation, mainly due to Cybersickness (CS) issues. In this work, we first present a detailed review about possible causes of CS. Following, we propose a novel CS prediction solution. Our system is able to suggest if the user may be entering in the next moments of the application into an illness situation. We use Random Forest classifiers, based on a dataset we have produced. The CSPQ (Cybersickness Profile Questionnaire) is also proposed, which is used to identify the player's susceptibility to CS and the dataset construction. In addition, we designed two immersive environments for empirical studies where participants are asked to complete the questionnaire and describe (orally) the degree of discomfort during their gaming experience. Our data was achieved through 84 individuals on different days, using VR devices. Our proposal also allows us to identify which are the most frequent attributes (causes) in the observed discomfort situations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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