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用于 Unity 中情境感知虚拟现实应用开发的数据收集框架：以化身体现为例。

Data Collection Framework for Context-Aware Virtual Reality Application Development in Unity: Case of Avatar Embodiment.

机构信息

Department of Digital Media, Ajou University, Suwon 16499, Korea.

Smart Mobility Lab, B2B Advanced Technology Center, LG Electronics, Seoul 07796, Korea.

出版信息

Sensors (Basel). 2022 Jun 19;22(12):4623. doi: 10.3390/s22124623.

DOI:10.3390/s22124623
PMID:35746405
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9228658/
Abstract

Virtual Reality (VR) has been adopted as a leading technology for the metaverse, yet most previous VR systems provide one-size-fits-all experiences to users. Context-awareness in VR enables personalized experiences in the metaverse, such as improved embodiment and deeper integration of the real world and virtual worlds. Personalization requires context data from diverse sources. We proposed a reusable and extensible context data collection framework, ManySense VR, which unifies data collection from diverse sources for VR applications. ManySense VR was implemented in Unity based on extensible context data managers collecting data from data sources such as an eye tracker, electroencephalogram, pulse, respiration, galvanic skin response, facial tracker, and Open Weather Map. We used ManySense VR to build a context-aware embodiment VR scene where the user's avatar is synchronized with their bodily actions. The performance evaluation of ManySense VR showed good performance in processor usage, frame rate, and memory footprint. Additionally, we conducted a qualitative formative evaluation by interviewing five developers (two males and three females; mean age: 22) after they used and extended ManySense VR. The participants expressed advantages (e.g., ease-of-use, learnability, familiarity, quickness, and extensibility), disadvantages (e.g., inconvenient/error-prone data query method and lack of diversity in callback methods), future application ideas, and improvement suggestions that indicate potential and can guide future development. In conclusion, ManySense VR is an efficient tool for researchers and developers to easily integrate context data into their Unity-based VR applications for the metaverse.

摘要

虚拟现实 (VR) 已被采用为元宇宙的领先技术，但大多数以前的 VR 系统为用户提供一刀切的体验。VR 中的情境感知使元宇宙中的个性化体验成为可能，例如改善了实体感和对现实世界和虚拟世界的更深层次融合。个性化需要来自不同来源的情境数据。我们提出了一个可重复使用和可扩展的情境数据收集框架 ManySense VR，它统一了来自不同来源的数据收集，用于 VR 应用程序。ManySense VR 是在基于可扩展情境数据管理器的 Unity 中实现的，该管理器从眼动追踪器、脑电图、脉搏、呼吸、皮肤电反应、面部追踪器和 Open Weather Map 等数据源收集数据。我们使用 ManySense VR 构建了一个情境感知体现 VR 场景，其中用户的头像与他们的身体动作同步。ManySense VR 的性能评估显示，在处理器使用、帧率和内存占用方面表现良好。此外，我们通过采访五名开发人员（两名男性和三名女性；平均年龄：22 岁）对他们使用和扩展 ManySense VR 后进行了定性形成性评估。参与者表达了优势（例如，易用性、易学性、熟悉性、快速性和可扩展性）、劣势（例如，数据查询方法不方便/容易出错和回调方法缺乏多样性）、未来应用想法和改进建议，这些都表明了潜力，并可以指导未来的发展。总之，ManySense VR 是研究人员和开发人员的有效工具，可方便地将情境数据集成到基于 Unity 的 VR 应用程序中，用于元宇宙。

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