Parallel view-dependent tessellation of Catmull-Clark subdivision surfaces

Anjul Patney, Mohamed S. Ebeida, John Douglas Owens
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引用次数: 45

Abstract

We present a strategy for performing view-adaptive, crack-free tessellation of Catmull-Clark subdivision surfaces entirely on programmable graphics hardware. Our scheme extends the concept of breadth-first subdivision, which up to this point has only been applied to parametric patches. While mesh representations designed for a CPU often involve pointer-based structures and irregular perelement storage, neither of these is well-suited to GPU execution. To solve this problem, we use a simple yet effective data structure for representing a subdivision mesh, and design a careful algorithm to update the mesh in a completely parallel manner. We demonstrate that in spite of the complexities of the subdivision procedure, real-time tessellation to pixel-sized primitives can be done. Our implementation does not rely on any approximation of the limit surface, and avoids both subdivision cracks and T-junctions in the subdivided mesh. Using the approach in this paper, we are able to perform real-time subdivision for several static as well as animated models. Rendering performance is scalable for increasingly complex models.
Catmull-Clark细分曲面的平行视图相关镶嵌
我们提出了一种完全在可编程图形硬件上执行视图自适应,无裂纹的Catmull-Clark细分表面镶嵌的策略。我们的方案扩展了宽度优先细分的概念,到目前为止,它只应用于参数补丁。虽然为CPU设计的网格表示通常涉及基于指针的结构和不规则的元素存储,但这两者都不适合GPU执行。为了解决这个问题,我们使用一种简单而有效的数据结构来表示细分网格,并设计了一种谨慎的算法来以完全并行的方式更新网格。我们证明,尽管细分过程的复杂性,实时镶嵌到像素大小的原语可以做到。我们的实现不依赖于极限表面的任何近似,并且避免了细分网格中的细分裂纹和t型结。使用本文的方法,我们能够对几个静态和动画模型进行实时细分。对于日益复杂的模型,渲染性能是可伸缩的。
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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