动态多光采样实时光线跟踪

Pierre Moreau, M. Pharr, Petrik Clarberg
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引用次数: 28

摘要

蒙特卡罗光线追踪提供了大量区域光源渲染场景的能力——灯光可以随机采样,阴影可以通过追踪光线来解释,而不是使用阴影地图或其他基于光栅化的技术,这些技术不能缩放到许多灯光或与区域灯光一起工作。目前的gpu只能以实时帧速率追踪每像素的几条光线,这使得有必要将采样集中在重要的光源上。虽然最先进的离线渲染算法在光源上构建分层数据结构,使其能够根据其重要性进行采样,但它们缺乏对动态场景的有效支持。提出了一种基于实时渲染的分层光采样数据结构维护算法。我们的方法基于两级BVH层次结构,减少了部分层次结构更新的成本。我们表明,这种方法可以在每帧从头开始重建整个层次结构的6%以内给出误差,同时速度提高了两个数量级,对于在现代GPU上具有数千个移动光源的场景,每帧层次结构更新需要不到1毫秒。此外,我们表明,通过时空滤波,我们的方法可以在每帧16.1毫秒的时间内用光线跟踪阴影渲染具有数千个光源的复杂场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic many-light sampling for real-time ray tracing
Monte Carlo ray tracing offers the capability of rendering scenes with large numbers of area light sources---lights can be sampled stochastically and shadowing can be accounted for by tracing rays, rather than using shadow maps or other rasterization-based techniques that do not scale to many lights or work well with area lights. Current GPUs only afford the capability of tracing a few rays per pixel at real-time frame rates, making it necessary to focus sampling on important light sources. While state-of-the-art algorithms for offline rendering build hierarchical data structures over the light sources that enable sampling them according to their importance, they lack efficient support for dynamic scenes. We present a new algorithm for maintaining hierarchical light sampling data structures targeting real-time rendering. Our approach is based on a two-level BVH hierarchy that reduces the cost of partial hierarchy updates. Performance is further improved by updating lower-level BVHs via refitting, maintaining their original topology We show that this approach can give error within 6% of recreating the entire hierarchy from scratch at each frame, while being two orders of magnitude faster, requiring less than 1 ms per frame for hierarchy updates for a scene with thousands of moving light sources on a modern GPU. Further, we show that with spatiotemporal filtering, our approach allows complex scenes with thousands of lights to be rendered with ray-traced shadows in 16.1 ms per frame.
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