Real-time Subsurface Control Variates: Temporally Stable Adaptive Sampling

Author/Creator ORCID

Date

2021-04-28

Department

Program

Citation of Original Publication

Tiantian Xie and Marc Olano. 2021. Real-time Subsurface Control Variates: Temporally Stable Adaptive Sampling. Proc. ACM Comput. Graph. Interact. Tech. 4, 1, Article 2 (April 2021), 18 pages. https://doi.org/10.1145/3451265

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Abstract

Real-time adaptive sampling is a new technique recently proposed for efficient importance sampling in realtime Monte Carlo sampling in subsurface scattering. It adaptively places samples based on variance tracking to help escape the uncanny valley of subsurface rendering. However, the occasional performance drop due to temporal lighting dynamics (e.g., guns or lights turning on and off) could hinder adoption in games or other applications where smooth high frame rate is preferred. In this paper we propose a novel usage of Control Variates (CV) in the sample domain instead of shading domain to maintain a consistent low pass time. Our algorithm seamlessly reduces to diffuse with zero scattering samples for sub-pixel scattering. We propose a novel joint-optimization algorithm for sample count and CV coefficient estimation. The main enabler is our novel time-variant covariance updating method that helps remove the effect of recent temporal dynamics from variance tracking. Since bandwidth is critical in real-time rendering, a solution without adding any extra textures is also provided.