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A Scalable Framework for Distributed Virtual Reality Using Heterogeneous Processors

机译:使用异构处理器的分布式虚拟现实的可扩展框架

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We propose a scalable framework for virtual reality systems in a distributed environment. As the application scope of and member participation in a virtual environment increase, information sharing among geographically distributed users becomes critical and challenging. In the proposed framework, we partition the virtual environment into a group of cells and upload them to a number of heterogeneous Internet nodes. When a user sends a request to explore the distant virtual environment, visible cells will be identified and processed in parallel to produce a minimal amount of imagery results for remote transmission. To ensure scalability, we extend our scalable occlusion culling scheme using Plenoptic Opacity Function to speed up the identification process of visible cells in a virtual environment. We perform effective occlusion culling in two passes based on a non-binary opacity definition. Our experimental results justify both the efficiency and scalability of our framework in exploring large-scale virtual environments.
机译:我们为分布式环境中的虚拟现实系统提出了一个可扩展的框架。随着虚拟环境的应用范围和成员参与度的增加,地理上分散的用户之间的信息共享变得至关重要且具有挑战性。在提出的框架中,我们将虚拟环境划分为一组单元,并将其上载到多个异构Internet节点。当用户发出探索遥远的虚拟环境的请求时,将识别并并行处理可见的单元,以生成最少数量的图像结果以进行远程传输。为了确保可扩展性,我们使用全光不透明度功能扩展了可扩展的遮挡剔除方案,以加快虚拟环境中可见细胞的识别过程。我们基于非二进制不透明度定义在两遍中执行有效遮挡剔除。我们的实验结果证明了在探索大规模虚拟环境中我们框架的效率和可扩展性都是合理的。

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