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Real-time GPU surface curvature estimation.

机译:实时GPU表面曲率估计。

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摘要

Surface curvature is used in a number of areas in computer graphics including mesh simplification, surface modeling and denoising, feature detection, and non-photorealistic line drawing techniques. Most applications must estimate surface curvature, due to the use of discrete models such as triangular meshes. Until recently, curvature estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. More computational work is being done directly on the GPU, and it is increasingly common for object geometry to only exist in GPU memory. Examples include vertex skinned animations, isosurfaces from GPU-based surface reconstruction algorithms, or triangular meshes generated by hardware tessellation units.;All of these types of geometry can be large in size and transferring the data to the CPU is cost prohibitive in interactive applications, especially if the mesh changes every frame. Thus, for static models, CPU algorithms for curvature estimation are a reasonable choice, but for models where the object geometry only resides on the GPU, CPU algorithms limit performance. I introduce a GPU algorithm for estimating curvature in real-time on arbitrary triangular meshes residing in GPU memory. I test my algorithm in a line drawing system with a vertex-skinned animation system and a GPU-based isosurface extraction system.
机译:表面曲率用于计算机图形学的许多领域,包括网格简化,表面建模和去噪,特征检测以及非照片级线条绘制技术。由于使用了离散模型(例如三角形网格),大多数应用程序必须估计表面曲率。直到最近,曲率估计还仅限于CPU算法,这迫使对象几何形状驻留在主存储器中。直接在GPU上进行更多的计算工作,对象几何仅存在于GPU内存中变得越来越普遍。例子包括顶点蒙皮动画,基于GPU的曲面重建算法的等值曲面或由硬件细分单元生成的三角形网格。所有这些类型的几何图形都可能很大,并且在交互式应用程序中将数据传输到CPU的成本很高,尤其是当网格每帧更改时。因此,对于静态模型,用于曲率估计的CPU算法是一个合理的选择,但是对于对象几何仅位于GPU上的模型,CPU算法会限制性能。我介绍了一种GPU算法,用于实时估计GPU内存中任意三角形网格上的曲率。我在带有顶点皮肤动画系统和基于GPU的等值面提取系统的线描系统中测试我的算法。

著录项

  • 作者

    Griffin, Wesley.;

  • 作者单位

    University of Maryland, Baltimore County.;

  • 授予单位 University of Maryland, Baltimore County.;
  • 学科 Computer Science.
  • 学位 M.S.
  • 年度 2010
  • 页码 66 p.
  • 总页数 66
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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