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dc.contributor.authorZhao, Shuang
dc.contributor.authorWu, Lifan
dc.contributor.authorDurand, Frédo
dc.contributor.authorRamamoorthi, Ravi
dc.date.accessioned2021-10-27T20:06:08Z
dc.date.available2021-10-27T20:06:08Z
dc.date.issued2016
dc.identifier.urihttps://hdl.handle.net/1721.1/134677
dc.description.abstract© 2016 ACM. Volumetric micro-appearance models have provided remarkably high-quality renderings, but are highly data intensive and usually require tens of gigabytes in storage. When an object is viewed from a distance, the highest level of detail offered by these models is usually unnecessary, but traditional linear downsampling weakens the object's intrinsic shadowing structures and can yield poor accuracy. We introduce a joint optimization of single-scattering albedos and phase functions to accurately downsample heterogeneous and anisotropic media. Our method is built upon scaled phase functions, a new representation combining abledos and (standard) phase functions. We also show that modularity can be exploited to greatly reduce the amortized optimization overhead by allowing multiple synthesized models to share one set of downsampled parameters. Our optimized parameters generalize well to novel lighting and viewing configurations, and the resulting data sets offer several orders of magnitude storage savings.
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.isversionof10.1145/2980179.2980228
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceother univ website
dc.titleDownsampling scattering parameters for rendering anisotropic media
dc.typeArticle
dc.identifier.citationZhao, Shuang, et al. "Downsampling Scattering Parameters for Rendering Anisotropic Media." Acm Transactions on Graphics 35 6 (2016): 11.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalACM Transactions on Graphics
dc.eprint.versionAuthor's final manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2019-05-29T12:50:59Z
dspace.orderedauthorsZhao, S; Wu, L; Durand, F; Ramamoorthi, R
dspace.date.submission2019-05-29T12:51:02Z
mit.journal.volume35
mit.journal.issue6
mit.metadata.statusAuthority Work and Publication Information Needed


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