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arXiv 2108.09538cs.HC
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利用轨迹压缩率预测虚拟现实游戏中的电脑病变化

Using Trajectory Compression Rate to Predict Changes in Cybersickness in Virtual Reality Games

Diego Monteiro, Hai-Ning Liang, Xiaohang Tang, Pourang Irani

摘要:

在虚拟现实(VR)应用(如游戏)中以快速、精确、非侵入性和非破坏性的方式识别网络病仍然具有挑战性。有几个因素会导致电脑病,它们的识别将有助于找到它的起源,防止或减少它。其中一个因素是虚拟运动。运动,无论是物理的还是虚拟的,都可以以不同的形式表现出来。一种表示和存储它的方法是使用时间注释的点序列。由于序列消耗内存,因此通常最好以压缩形式保存它。压缩允许消除冗余数据,同时仍然保留速度和方向的变化。由于VR中方向和速度的变化可能与晕机有关,因此压缩率的变化可能表明晕机水平的变化。在这项研究中,我们探讨是否可以量化虚拟运动的变化,以估计VR用户的晕电水平的变化。我们研究了两款VR游戏中运动数据压缩率的变化与游戏过程中捕获的玩家晕电水平变化之间的相关性。我们的研究结果表明:(1)压缩率的变化与晕电病之间存在明显的相关性;(2)机器学习方法可用于识别这些变化。最后,从第二个实验的结果表明,我们的方法是可行的,在游戏和其他VR应用程序,涉及运动的晕网推理。

英文摘要:

Identifying cybersickness in virtual reality (VR) applications such as games in a fast, precise, non-intrusive, and non-disruptive way remains challenging. Several factors can cause cybersickness, and their identification will help find its origins and prevent or minimize it. One such factor is virtual movement. Movement, whether physical or virtual, can be represented in different forms. One way to represent and store it is with a temporally annotated point sequence. Because a sequence is memory-consuming, it is often preferable to save it in a compressed form. Compression allows redundant data to be eliminated while still preserving changes in speed and direction. Since changes in direction and velocity in VR can be associated with cybersickness, changes in compression rate can likely indicate changes in cybersickness levels. In this research, we explore whether quantifying changes in virtual movement can be used to estimate variation in cybersickness levels of VR users. We investigate the correlation between changes in the compression rate of movement data in two VR games with changes in players' cybersickness levels captured during gameplay. Our results show (1) a clear correlation between changes in compression rate and cybersickness, and(2) that a machine learning approach can be used to identify these changes. Finally, results from a second experiment show that our approach is feasible for cybersickness inference in games and other VR applications that involve movement.

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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