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Optimization and Manipulation of Contextual Mutual Spaces for Multi-User Virtual and Augmented Reality Interaction

机译:多用户虚拟现实和增强现实交互的上下文互空间的优化和操纵

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Spatial computing experiences are physically constrained by the geometry and semantics of the local user environment. This limitation is elevated in remote multi-user interaction scenarios, where finding a common virtual ground physically accessible for all participants becomes challenging. Locating a common accessible virtual ground is difficult for the users themselves, particularly if they are not aware of the spatial properties of other participants. In this paper, we introduce a framework to generate an optimal mutual virtual space for a multi-user interaction setting where remote users’ room spaces can have different layout and sizes. The framework further recommends movement of surrounding furniture objects that expand the size of the mutual space with minimal physical effort. Finally, we demonstrate the performance of our solution on real-world datasets and also a real HoloLens application. Results show the proposed algorithm can effectively discover optimal shareable space for multi-user virtual interaction and hence facilitate remote spatial computing communication in various collaborative workflows.
机译:空间计算体验在物理上受到本地用户环境的几何形状和语义的限制。在远程多用户交互方案中,这种限制会增加,在这种情况下,找到所有参与者均可物理访问的公共虚拟地面变得非常困难。对于用户自己而言,很难找到通用的可访问虚拟地面,尤其是如果他们不了解其他参与者的空间特性时。在本文中,我们介绍了一个框架,该框架可为多用户交互设置生成最佳的相互虚拟空间,其中远程用户的房间空间可以具有不同的布局和大小。该框架还建议移动周围的家具对象,以最小的体力来扩大相互空间的大小。最后,我们演示了我们的解决方案在真实数据集以及实际HoloLens应用程序上的性能。结果表明,该算法可以有效地发现用于多用户虚拟交互的最佳可共享空间,从而促进各种协作工作流中的远程空间计算通信。

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