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Geometry-Aware Metropolis Light Transport

Hisanari Otsu, Johannes Hanika, Toshiya Hachisuka, and Carsten Dachsbacher

To appear in ACM Transactions on Graphics 37(6) (Proceedings of SIGGRAPH Asia 2018)

Equal-time comparison (30 minutes) of the \emph{Ajar door} scene, which is only illuminated by light leaking through the door. Left: Reference image computed with bidirectional path tracing. Middle: Image rendered with Metropolis light transport (MLT) [Veach and Guibas 1997]. Right: Image rendered with our geometry-aware Metropolis light transport (GeoMLT). Note how MLT has difficulties as the mutation of the paths passing through the gap tends to be rejected because of changing visibility. Our approach adaptively controls the mutation size according to the geometry information surrounding each path segment.


Markov chain Monte Carlo (MCMC) rendering utilizes a sequence of correlated path samples which is obtained by iteratively mutating the current state to the next. The efficiency of MCMC rendering depends on how well the mutation strategy is designed to adapt to the local structure of the state space. We present a novel MCMC rendering method that automatically adapts the step sizes of the mutations to the geometry of the rendered scene. Our geometry-aware path space perturbation largely avoids tentative samples with zero contribution due to occlusion. Our method limits the mutation step size by estimating the maximum opening angle of a cone, centered around a segment of a light transport path, where no geometry obstructs visibility. As this cone estimation introduces a considerable overhead if done naively, to make our approach efficient, we discuss and analyze fast approximate methods for cone angle estimation which utilize the acceleration structure already present for the ray-geometry intersection. Our new approach, integrated into the framework of Metropolis light transport, can achieve results with lower error and less artifact in equal time compared to current path space mutation techniques.


to appear