Efficient Divide-And-Conquer Ray Tracing using Ray Sampling

Abstract

Divide-and-conquer ray tracing (DACRT) methods solve intersection problems between large numbers of rays and primitives by recursively subdividing the problem size until it can be easily solved. Previous DACRT methods subdivide the intersection problem based on the distribution of primitives only, and do not exploit the distribution of rays, which results in a decrease of the rendering performance especially for high resolution images with antialiasing. We propose an efficient DACRT method that exploits the distribution of rays by sampling the rays to construct an acceleration data structure. To accelerate ray traversals, we have derived a new cost metric which is used to avoid inefficient subdivision of the intersection problem where the number of rays is not sufficiently reduced. Our method accelerates the tracing of many types of rays (primary rays, less coherent secondary rays, random rays for path tracing) by a factor of up to 2 using ray sampling.