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A POINT-BASED ASYNCHRONOUS REMOTE VISUALIZATION FRAMEWORK FOR REAL-TIME VIRTUAL REALITY

机译:实时虚拟现实的基于点的异步远程可视化框架

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摘要

High speed interactive virtual reality (VR) exploration of scientific datasets is a challenge when the visualization is computationally expensive. This paper presents a point-based remote visualization pipeline for real-time virtual reality (VR) with asynchronous client-server coupling. Steered by the client-end frustum request, the remote server samples the original dataset into 3D point samples and sends them back to the client for view updating. From every view updating frame, the client incrementally builds up a point-based geometry under an octree-based space partition hierarchy. At every view-reconstruction frame, the client continuously splats the available points onto the screen with efficient occlusion culling and view-dependent level of detail (LOD) control. An experimental visualization framework with a server-end computer cluster and a client-end head-tracked autostereo VR desktop display is used to visualize large-scale mesh datasets and ray-traced 4D Julia set datasets. The overall performance of the VR view reconstruction is about 15 fps and independent of the original dataset complexity.
机译:当可视化在计算上昂贵时,对科学数据集的高速交互式虚拟现实(VR)探索是一个挑战。本文提出了一种基于点的远程可视化管道,用于具有异步客户端-服务器耦合的实时虚拟现实(VR)。远程服务器受客户端客户端截锥体请求的控制,将原始数据集采样为3D点样本,并将其发送回客户端以进行视图更新。在每个视图更新框架中,客户端将在基于八叉树的空间分区层次结构下逐步构建基于点的几何。在每个视图重建框架中,客户端都会通过有效的遮挡剔除和与视图相关的详细程度(LOD)控制,将可用点连续显示在屏幕上。具有服务器端计算机集群和客户端头跟踪自动立体VR桌面显示的实验性可视化框架用于可视化大规模网格数据集和光线跟踪的4D Julia set数据集。 VR视图重建的整体性能约为15 fps,并且与原始数据集的复杂性无关。

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