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周圣川, 马纯永, 陈戈. 城市三维场景的逆过程式建模与混合渲染方法[J]. 计算机辅助设计与图形学学报, 2015, 27(1): 88-97.
引用本文: 周圣川, 马纯永, 陈戈. 城市三维场景的逆过程式建模与混合渲染方法[J]. 计算机辅助设计与图形学学报, 2015, 27(1): 88-97.
Zhou Shengchuan, Ma Chunyong, Chen Ge. An Inverse Procedural Modeling and Hybrid Rendering Approach for Large-Scale Urban Scenes Visualization[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(1): 88-97.
Citation: Zhou Shengchuan, Ma Chunyong, Chen Ge. An Inverse Procedural Modeling and Hybrid Rendering Approach for Large-Scale Urban Scenes Visualization[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(1): 88-97.

城市三维场景的逆过程式建模与混合渲染方法

An Inverse Procedural Modeling and Hybrid Rendering Approach for Large-Scale Urban Scenes Visualization

  • 摘要: 针对大规模城市场景受制于数据规模,难以实现完整场景的视觉无损渲染的问题,提出一种基于过程式纹理重构和混合层次细节(LOD)模型的渲染方法.首先提取纹理中的重复与对称特征,构造纹理的过程式语法表示,实现了约70%的数据压缩,并且用户可以直接控制过程式语法的生成;然后通过几何模型采样创建点、线和多边形混合的LOD表示并编码存储;最后根据屏幕空间投影面积选择LOD模型进行渲染.实验结果表明,与原始模型和几何LOD方法相比,该方法分别实现了约10倍和5倍的渲染加速,可以实时渲染城市级大场景;在大幅度提高渲染效率的同时,基于72个个体样本的用户感知评价测试和基于动态范围无关算法的自动化测试结果证明,该方法渲染结果的视觉质量与原始模型相比无显著差异,是一种视觉无损渲染方法.

     

    Abstract: A novel procedural modeling and hybrid level-of-detail rendering method is introduced for visually lossless urban scenes visualization. Our user-assisted inverse procedural modeling approach allows the user to exploit repetitions and symmetries of facades to create a split grammar representation of the input, which achieved a 70% compression factor averagely. We extract lines and points from the input models and provide their simplifications encoded in a data structure that allows for a quick and automatic LOD selection. Projected area is used as a LOD selector to combine points, lines, and polygon models that contain procedural textures. Our implementation shows a 10 times speed-up as compared to the ground truth rendered as full geometry, and is about 5 times faster compared to the geometric LOD. The quality of the results is indistinguishable from the original that was confirmed by a user study conducted with 72 subjects and an automated dynamic range independent metric.

     

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