探索和模拟虚拟现实技术对转向行为的方向性影响

Yushi Wei;Kemu Xu;Yue Li;Lingyun Yu;Hai-Ning Liang
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摘要

转向是交互式虚拟现实(VR)系统中的一项基本任务。先前的研究表明,移动方向会显著影响用户在转向任务中的行为,不同的交互环境(VE)会导致不同的行为模式,如平板电脑和个人电脑。然而,其对 VR 环境的影响仍有待探索。鉴于转向任务(包括菜单调整和物体操作)在 VE 中的广泛应用,本研究试图了解方向效应并建立模型,重点关注 VE 中典型的徒手交互。本文介绍了两项研究的结果。第一项研究收集了四类行为数据:移动时间、平均移动速度、成功率和重新输入时间。根据结果,我们研究了移动方向的影响,并建立了 Sθ 模型。然后,我们通过第一次研究收集的数据对模型进行了实证评估。结果证明,我们提出的模型在所有指标上都达到了最佳性能(r2 > 0.95),在预测准确率方面比原来的转向法提高了 15%以上。接下来,我们通过另一项改变设备和转向方向的研究进一步验证了 Sθ 模型。与之前的评估结果一致,该模型在预测运动时间和速度方面继续表现出最佳性能。最后,根据研究结果,我们为虚拟现实设备中的转向任务提出了设计建议,以提高用户体验和交互效率。
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Exploring and Modeling Directional Effects on Steering Behavior in Virtual Reality
Steering is a fundamental task in interactive Virtual Reality (VR) systems. Prior work has demonstrated that movement direction can significantly influence user behavior in the steering task, and different interactive environments (VEs) can lead to various behavioral patterns, such as tablets and PCs. However, its impact on VR environments remains unexplored. Given the widespread use of steering tasks in VEs, including menu adjustment and object manipulation, this work seeks to understand and model the directional effect with a focus on barehand interaction, which is typical in VEs. This paper presents the results of two studies. The first study was conducted to collect behavioral data with four categories: movement time, average movement speed, success rate, and reenter times. According to the results, we examined the effect of movement direction and built the SθModel. We then empirically evaluated the model through the data collected from the first study. The results proved that our proposed model achieved the best performance across all the metrics (r2 > 0.95), with more than 15% improvement over the original Steering Law in terms of prediction accuracy. Next, we further validated the SθModel by another study with the change of device and steering direction. Consistent with previous assessments, the model continues to exhibit optimal performance in both predicting movement time and speed. Finally, based on the results, we formulated design recommendations for steering tasks in VEs to enhance user experience and interaction efficiency.
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