论文标题
手动跟踪作为虚拟现实中一种互动方式对用户体验的影响
Influence of Hand Tracking as a way of Interaction in Virtual Reality on User Experience
论文作者
论文摘要
随着对虚拟现实的兴趣不断上升,可用设备的快速开发和改进,相互作用的新功能就变得可用。其中一个变得非常受欢迎的是手工跟踪,作为代替虚拟世界中互动的控制器的想法。该实验旨在使用控制器或手动跟踪比较VR中的不同交互类型。参与者必须在这些游戏中玩具有各种任务的两个简单VR游戏 - 抓取对象或打字数字。在演奏时,他们使用的是与手和控制器的不同可视化的互动。这项研究的重点是研究这两个简单任务的不同互动(控制器与手动跟踪)的用户体验。结果表明,不同的相互作用类型在统计学上显着影响了自我评估Manikin(SAM)的情绪,在该情绪中,用于手工跟踪的参与者感觉较高,但唤醒和优势较低。此外,据报道,抢劫的任务类型更现实,参与者的存在更高。令人惊讶的是,参与者将交互类型与控制器进行了评分,在该控制器上,手和控制器在统计上最喜欢的地方都可以看到。最后,对这两个任务的手跟踪都按系统可用性量表(SUS)量表进行了评分,并且对任务键入的手部跟踪在统计学上被评为统计上的可用性更大。这些结果可以推动进一步的研究,从长远来看,这些结果有助于帮助为任务选择最匹配的互动方式。
With the rising interest in Virtual Reality and the fast development and improvement of available devices, new features of interactions are becoming available. One of them that is becoming very popular is hand tracking, as the idea to replace controllers for interactions in virtual worlds. This experiment aims to compare different interaction types in VR using either controllers or hand tracking. Participants had to play two simple VR games with various types of tasks in those games - grabbing objects or typing numbers. While playing, they were using interactions with different visualizations of hands and controllers. The focus of this study was to investigate user experience of varying interactions (controller vs. hand tracking) for those two simple tasks. Results show that different interaction types statistically significantly influence reported emotions with Self-Assessment Manikin (SAM), where for hand tracking participants were feeling higher valence, but lower arousal and dominance. Additionally, task type of grabbing was reported to be more realistic, and participants experienced a higher presence. Surprisingly, participants rated the interaction type with controllers where both where hands and controllers were visualized as statistically most preferred. Finally, hand tracking for both tasks was rated with the System Usability Scale (SUS) scale, and hand tracking for the task typing was rated as statistically significantly more usable. These results can drive further research and, in the long term, contribute to help selecting the most matching interaction modality for a task.