Specular Manifold Bisection Sampling for Caustics Rendering

dc.contributor.authorJhang, Jia-Wunen_US
dc.contributor.authorChang, Chun-Faen_US
dc.contributor.editorUmetani, Nobuyukien_US
dc.contributor.editorWojtan, Chrisen_US
dc.contributor.editorVouga, Etienneen_US
dc.date.accessioned2022-10-04T06:40:50Z
dc.date.available2022-10-04T06:40:50Z
dc.date.issued2022
dc.description.abstractWe propose Specular Manifold Bisection Sampling (SMBS), an improved version of Specular Manifold Sampling (SMS) [ZGJ20]. SMBS is inspired by the small and large mutations in Metropolis Light Transport (MLT) [VG97]. While the Jacobian Matrix of the original SMS method performs well in local convergence (the small mutation), it might fail to find a valid manifold path when the ray deviates too much from the light or bounces from a complex surface. Our proposed SMBS method adds a large mutation step to avoid such a problematic convergence to the local minimum. The results show SMBS can find valid manifold paths in fewer iterations and also find more valid manifold paths. In scenes with complex reflective or refractive surfaces, our method achieves nearly twice or more improvement when measured in manifold walk success rate (SR) and root mean square error (RMSE).en_US
dc.description.number7
dc.description.sectionheadersRendering - Sampling
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14673
dc.identifier.issn1467-8659
dc.identifier.pages247-254
dc.identifier.pages8 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14673
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14673
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies → Rendering
dc.subjectComputing methodologies → Rendering
dc.titleSpecular Manifold Bisection Sampling for Caustics Renderingen_US
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