Efficient Visibility Heuristics for kd-trees Using the RTSAH

Matthias Moulin, Niels Billen, P. Dutré
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引用次数: 1

Abstract

Acceleration data structures such as kd-trees aim at reducing the per-ray cost which is crucial for rendering performance. The de-facto standard for constructing kd-trees, the Surface Area Heuristic (SAH), does not take ray termination into account and instead assumes rays never hit a geometric primitive. The Ray Termination Surface Area Heuristic (RTSAH) is a cost metric originally used for determining the traversal order of the voxels for occlusion rays that takes ray termination into account. We adapt this RTSAH to building kd-trees that aim at reducing the per-ray cost of rays. Our build procedure has the same overall computational complexity and considers the same finite set of splitting planes as the SAH. By taking ray termination into account, we favor cutting off child voxels which are not or hardly visible to each other. This results in fundamentally different and more qualitative kd-trees compared to the SAH.
基于RTSAH的kd树可视化启发式算法
加速数据结构(如kd-trees)旨在降低对渲染性能至关重要的每条射线成本。构造kd树的事实标准,表面积启发式(SAH),不考虑射线终止,而是假设射线从未击中几何原语。射线终止表面积启发式(RTSAH)是一种成本度量,最初用于确定考虑射线终止的遮挡射线体素的遍历顺序。我们将此RTSAH应用于构建旨在降低射线每条射线成本的kd树。我们的构建过程具有与SAH相同的总体计算复杂性,并且考虑相同的有限分割平面集。考虑到射线终止,我们倾向于切断彼此不可见或几乎不可见的子体素。与SAH相比,这导致了本质上不同且更定性的kd树。
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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