射线追踪参数曲面的压缩表示

Kai Selgrad, Alexander Lier, Magdalena Martinek, Christoph Buchenau, M. Guthe, Franziska Kranz, Henry Schäfer, M. Stamminger
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引用次数: 1

摘要

参数化曲面是计算机辅助设计和电影制作中必不可少的建模工具。尽管它们的使用在工业中已经很好地建立起来,但生成光线跟踪图像在时间和内存消耗方面增加了显著的成本。光线追踪这样的表面通常是通过对表面进行细分或转换为多边形表示来完成的。然而,即时细分在计算上是非常昂贵的,而多边形网格需要大量的内存。对于具有位移的参数曲面来说,这是一个特殊的问题,需要非常精细的镶嵌来忠实地表示形状。因此,内存限制是生产呈现中的主要挑战。在本文中,我们提出了一种新的解决方案。我们提出了一种基于参数补丁的先验边界体层次结构(BVHs)的压缩方案,该方案将层次结构所需的数据减少了多达48倍。我们进一步提出了一种不需要叶片几何形状的近似评估方法,其内存消耗总体上比索引面部集上的常规bvh减少60倍,比已建立的最先进的压缩方案减少16倍。或者,我们的压缩可以简单地应用于标准BVH,同时保持叶片的几何形状,与当前方法相比,压缩率高达2:1。尽管解压缩在遍历过程中会产生额外的成本,但我们可以在具有竞争性渲染时间的内存受限GPU上管理非常复杂的场景。
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A compressed representation for ray tracing parametric surfaces
Parametric surfaces are an essential modeling tool in computer aided design and movie production. Even though their use is well established in industry, generating ray-traced images adds significant cost in time and memory consumption. Ray tracing such surfaces is usually accomplished by subdividing the surfaces on the fly, or by conversion to a polygonal representation. However, on-the-fly subdivision is computationally very expensive, whereas polygonal meshes require large amounts of memory. This is a particular problem for parametric surfaces with displacement, where very fine tessellation is required to faithfully represent the shape. Hence, memory restrictions are the major challenge in production rendering. In this article, we present a novel solution to this problem. We propose a compression scheme for a priori Bounding Volume Hierarchies (BVHs) on parametric patches, that reduces the data required for the hierarchy by a factor of up to 48. We further propose an approximate evaluation method that does not require leaf geometry, yielding an overall reduction of memory consumption by a factor of 60 over regular BVHs on indexed face sets and by a factor of 16 over established state-of-the-art compression schemes. Alternatively, our compression can simply be applied to a standard BVH while keeping the leaf geometry, resulting in a compression rate of up to 2:1 over current methods. Although decompression generates additional costs during traversal, we can manage very complex scenes even on the memory restrictive GPU at competitive render times.
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