Web3D-Based Online Walkthrough of Large-Scale Underground Scenes

Xiaojun Liu, Ning Xie, Jinyuan Jia
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引用次数: 1

Abstract

Large-scale scenes' processing has become the major trend today. We mainly address the online walkthrough of Large-scale underground (UG) scenes in this paper. Taking into account the characteristics of UG scene, we first propose a lightweight preprocessing to optimize the raw UG scene and unify the raw data with scene, sub-scene and simple model. Then we generate a three-layered grid structure for organizing the scene to facilitate the visibility culling and data accessing. Finally, we design two scene management strategies, named SOI-Exterior Shell and Portal-Interior Shell, and integrate our methods in an experimental prototype. The experimental result shows that our method can remove a large amount of redundancies from the raw data, reduce resource consumption greatly and make it possible to walkthrough in large-scale UG scenes online without any web browsers plugins.
基于web3d的大型地下场景在线演练
大规模场景的处理已成为当今的主要趋势。本文主要研究大规模地下场景的在线演练。针对UG场景的特点,首先提出了一种轻量级的预处理方法,对原始UG场景进行优化,实现了原始数据与场景、子场景和简单模型的统一。然后,我们生成一个三层网格结构来组织场景,以方便可见性剔除和数据访问。最后,我们设计了两个场景管理策略,soi - external Shell和Portal-Interior Shell,并将我们的方法整合到一个实验原型中。实验结果表明,该方法可以去除原始数据中的大量冗余,大大降低了资源消耗,并且可以在不使用任何web浏览器插件的情况下在线进行大规模UG场景的演练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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