Fan, ShaohuaChenney, StephenLai, Yu-chiKavita Bala and Philip Dutre2014-01-272014-01-2720053-905673-23-11727-3463https://doi.org/10.2312/EGWR/EGSR05/127-138We present Metropolis Photon Sampling (MPS), a visual importance-driven algorithm for populating photon maps. Photon Mapping and other particle tracing algorithms fail if the photons are poorly distributed. Our approach samples light transport paths that join a light to the eye, which accounts for the viewer in the sampling process and provides information to improve photon storage. Paths are sampled with a Metropolis-Hastings algorithm that exploits coherence among important light paths. We also present a technique for including user selected paths in the sampling process without introducing bias. This allows a user to provide hints about important paths or reduce variance in specific parts of the image. We demonstrate MPS with a range of scenes and show quantitative improvements in error over standard Photon Mapping and Metropolis Light Transport.Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism Color, shading, shadowing, and texture