filename     : Xu24a.pdf
entry        : toappear
conference   : SIGGRAPH Asia 2024, Tokyo, Japan, 3-6 December, 2024
pages        : 1-17
year         : 2024
month        : December
title        : Volume Scattering Probability Guiding
subtitle     :
author       : Kehan Xu, Sebastian Herholz, Marco Manzi, Marios Papas, and Markus Gross
booktitle    : ACM Transactions on Graphics (TOG) - SIGGRAPH Asia 2024 Conference Proceedings
ISSN/ISBN    : 
editor       : ACM New York, NY, USA
publisher    : Association for Computing Machinery
publ.place   :
volume       : 43
issue        : 6
language     : English
keywords     : rendering, ray tracing
abstract     : Simulating the light transport of volumetric effects poses significant challenges and costs, especially in the presence of heterogeneous volumes. Generating stochastic paths for volume rendering involves multiple decisions, and previous works mainly focused on directional and distance sampling, where the volume scattering probability (VSP), i.e., the probability of scattering inside a volume, is indirectly determined as a byproduct of distance sampling. We demonstrate that direct control over the VSP can significantly improve efficiency and present an unbiased volume rendering algorithm based on an existing resampling framework for precise control over the VSP. Compared to the previous state-of-the-art, which can only increase the VSP without guaranteeing to reach the desired value, our method also supports decreasing the VSP. We further present a data-driven guiding framework to efficiently learn and query an approximation of the optimal VSP everywhere in the scene without the need for user control. Our approach can easily be combined with existing path-guiding methods for directional sampling at minimal overhead and shows significant improvements over the state-of-the-art in various complex volumetric lighting scenarios.