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dc.contributor.authorGolovinskiy, Aleksey
dc.contributor.authorMatusik, Wojciech
dc.contributor.authorPfister, Hanspeter
dc.contributor.authorRusinkiewicz, Szymon
dc.contributor.authorFunkhouser, Thomas
dc.date.accessioned2010-05-19T14:24:36Z
dc.date.issued2006
dc.identifier.citationGolovinskiy, Aleksey, Wojciech Matusik, Hanspeter Pfister, Szymon Rusinkiewicz, and Thomas Funkhouser. 2006. A statistical model for synthesis of detailed facial geometry. In Proceedings International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2006 Papers: July 30 - August 03, 2006, Boston, Massachusetts, 1025-1034. New York, N.Y.: ACM Press. Also published in ACM Transactions on Graphics 25(3): 1025-1034.en_US
dc.identifier.isbn1-59593-364-6en_US
dc.identifier.issn0730-0301en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4101996
dc.description.abstractDetailed surface geometry contributes greatly to the visual realism of 3D face models. However, acquiring high-resolution face geometry is often tedious and expensive. Consequently, most face models used in games, virtual reality, or computer vision look unrealistically smooth. In this paper, we introduce a new statistical technique for the analysis and synthesis of small three-dimensional facial features, such as wrinkles and pores. We acquire high-resolution face geometry for people across a wide range of ages, genders, and races. For each scan, we separate the skin surface details from a smooth base mesh using displaced subdivision surfaces. Then, we analyze the resulting displacement maps using the texture analysis/synthesis framework of Heeger and Bergen, adapted to capture statistics that vary spatially across a face. Finally, we use the extracted statistics to synthesize plausible detail on face meshes of arbitrary subjects. We demonstrate the effectiveness of this method in several applications, including analysis of facial texture in subjects with different ages and genders, interpolation between high-resolution face scans, adding detail to low-resolution face scans, and adjusting the apparent age of faces. In all cases, we are able to re-produce fine geometric details consistent with those observed in high resolution scans.en_US
dc.description.sponsorshipEngineering and Applied Sciencesen_US
dc.language.isoen_USen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofdoi:10.1145/1141911.1141988en_US
dc.relation.isversionofdoi:10.1145/1179352.1141988en_US
dc.relation.hasversionhttp://gvi.seas.harvard.edu/sites/all/files/Golovinski06Statistical.pdfen_US
dash.licenseLAA
dc.subjectface modelingen_US
dc.subjecttexture synthesisen_US
dc.titleA Statistical Model for Synthesis of Detailed Facial Geometryen_US
dc.typeConference Paperen_US
dc.description.versionAccepted Manuscripten_US
dc.relation.journalACM Transactions on Graphicsen_US
dash.depositing.authorPfister, Hanspeter
dc.date.available2010-05-19T14:24:36Z
dc.identifier.doi10.1145/1141911.1141988*
dash.contributor.affiliatedPfister, Hanspeter
dc.identifier.orcid0000-0002-3620-2582


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