Pseudo-Marginal Metropolis Light Transport
2015 (English)In: Proceeding SA '15 SIGGRAPH Asia 2015 Technical Briefs, ACM Digital Library, 2015, 13:1-13:4 p.Conference paper (Other academic)
Accurate and efficient simulation of light transport in heterogeneous participating media, such as smoke, clouds and fire, plays a key role in the synthesis of visually interesting renderings for e.g. visual effects, computer games and product visualization. However, rendering of scenes with heterogenous participating with Metropolis light transport (MLT) algorithms have previously been limited to primary sample space methods or using biased approximations of the transmittance in the scene. This paper presents a new sampling strategy for Markov chain Monte Carlo (MCMC) methods, e.g. MLT, based on pseudo-marginal MCMC. Specifically, we show that any positive and unbiased estimator of the target distribution can replace the exact quantity to simulate a Markov Chain with a stationary distribution that has a marginal which is the exact target distribution of interest. This enables us to evaluate the transmittance function with recent unbiased estimators which leads to significantly shorter rendering times. Compared to previous work, relying on (biased) ray-marching for evaluating transmittance, our method enables simulation of longer Markov chains, a better exploration of the path space, and consequently less image noise, for a given computational budget. To demonstrate the usefulness of our pseudo-marginal approach, we compare it to representative methods for efficient rendering of anisotropic heterogeneous participating media and glossy transfer. We show that it performs significantly better in terms of image noise and rendering times compared to previous techniques. Our method is robust, and can easily be implemented in a modern renderer.
Place, publisher, year, edition, pages
ACM Digital Library, 2015. 13:1-13:4 p.
Computer Science Computer and Information Science
IdentifiersURN: urn:nbn:se:liu:diva-122586DOI: 10.1145/2820903.2820922ISBN: 978-1-4503-3930-8OAI: oai:DiVA.org:liu-122586DiVA: diva2:868265
The 8th ACM SIGGRAPH Conference and Exhibition, Asia Technical Briefs, 3-5 November, Kobe, Japan