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How the Presence and Size of Static Peripheral Blur Affects Cybersickness in Virtual Reality

机译:静态外围模糊的存在和大小如何影响虚拟现实中的胭脂节

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Cybersickness (CS) is one of the challenges that has hindered the widespread adoption of Virtual Reality and its applications. Consequently, a number of studies have focused on extensively understanding and reducing CS. Inspired by previous work that has sought to reduce CS using foveated rendering and Field of View (FOV) restrictions, we investigated how the presence and size of a static central window in peripheral FOV blurring affects CS. To facilitate this peripheral FOV blur, we applied a Gaussian blur effect in the display peripheral region, provisioning a full-resolution central window. Thirty participants took part in a three-session, within-subjects experiment, performing search and spatial updating tasks in a first-person, slow-walking, maze-traveling scenario. Two different central window sizes (small and large) were tested against a baseline condition that didn't feature display peripheral blurring. Results revealed that the baseline condition produced higher levels of CS than both conditions with a central window. While there were no significant differences between the small and large windows, we observed interaction effects suggesting an influence of window size on "adaptation to CS." When the central window is small, adaptation to CS seems to take more time but is more pronounced. The interventions had no effect on spatial updating and presence, but were detectable when the blurred area was larger (small central window). Lower sickness levels observed in both window conditions supports the use of peripheral FOV blurring to reduce CS, reducing our dependence on eye tracking. This being said, researchers must strive to find the right balance between window size and detectability to ensure seamless virtual experiences.
机译:Cyber​​ickness(CS)是阻碍了虚拟现实及其应用的广泛采用的挑战之一。因此,许多研究都集中在广泛的理解和减少CS。灵感来自以前的工作,我们试图使用FOVEATED渲染和视野(FOV)限制来减少CS,我们调查了外围FOV模糊的静态中心窗口的存在和大小如何影响CS。为了便于这种外围FOV模糊,我们在显示外围区域中应用了高斯模糊效果,配置了全分辨率的中心窗口。三十名参与者参加了一个三次会议,在一个主题内部实验,在第一人称,慢散,迷宫旅行场景中执行搜索和空间更新任务。测试两个不同的中央窗口尺寸(小型和大)以测试没有特征外围模糊的基线条件。结果表明,基线状况在中央窗口的条件下产生了更高水平的Cs。虽然小窗户之间没有显着差异,但我们观察到窗口大小对“适应CS的适应”影响互动效果。当中央窗口很小时,对CS的适应似乎需要更多的时间,但更明显。干预措施对空间更新和存在没有影响,但是当模糊区域更大时可检测到(小中央窗口)。在两个窗口条件下观察到的疾病水平都支持使用外围FOV模糊以降低CS,从而降低我们对眼睛跟踪的依赖。据说,研究人员必须努力在窗口大小和可检测性之间找到合适的平衡,以确保无缝虚拟体验。

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