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Stimulus Sampling With 360-Videos: Examining Head Movements, Arousal, Presence, Simulator Sickness, and Preference on a Large Sample of Participants and Videos
IEEE Transactions on Affective Computing ( IF 11.2 ) Pub Date : 2020-06-24 , DOI: 10.1109/taffc.2020.3004617
Hanseul Jun 1 , Mark Roman Miller 2 , Fernanda Herrera 1 , Byron Reeves 1 , Jeremy N. Bailenson 1
Affiliation  

As the public use of virtual reality (VR) scales, understanding how users engage across various sources of VR content is critical. 360-video is popular due to its ease of both creation and access. There are, however, few studies of 360-videos, and they suffer from three limitations. First, most studies rely on small and homogeneous samples of participants. Second, they tend to examine only a single 360-video, or a handful of them in a few exceptional cases. Third, very few studies trace participants’ VR use over multiple experiences. The current study examined a large sample of participants (511) and a large set of 360-videos (80). Each participant experienced 5 of the videos, and we tracked head movement in addition to self-report data on presence, arousal, simulator sickness, and future use intention for each video. This design allowed us to answer novel questions relating to individual differences of participants and changes in experience over time, and in general to present results of VR use at a scale not seen before in the literature. Moreover, the results suggest that looking at patterns across stimuli provide unique insights which are missed when looking only within a single piece of content.

中文翻译:

使用 360 视频进行刺激采样:检查大量参与者和视频样本的头部运动、唤醒、存在、模拟器疾病和偏好

随着虚拟现实 (VR) 的公众使用规模不断扩大,了解用户如何参与各种 VR 内容来源至关重要。360 度视频因其易于创建和访问而广受欢迎。然而,对 360 度视频的研究很少,它们受到三个限制。首先,大多数研究依赖于小而同质的参与者样本。其次,他们倾向于只检查一个 360 度视频,或者在少数例外情况下检查其中的一小部分。第三,很少有研究追踪参与者在多重体验中的 VR 使用情况。目前的研究检查了大量参与者 (511) 样本和大量 360 视频 (80)。每个参与者都体验了 5 个视频,除了每个视频的存在、唤醒、模拟器疾病和未来使用意图的自我报告数据外,我们还跟踪头部运动。这种设计使我们能够回答与参与者的个体差异和体验随时间变化有关的新问题,并且通常以文献中前所未有的规模呈现 VR 使用的结果。此外,结果表明,查看不同刺激的模式可以提供独特的见解,而这些见解在仅查看单个内容时会被遗漏。
更新日期:2020-06-24
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