Andrew Jones, Graham Fyffe, Xueming Yu, Alex Ma, Jay Busch, M. Bolas, P. Debevec
{"title":"Head-Mounted Photometric Stereo for Performance Capture","authors":"Andrew Jones, Graham Fyffe, Xueming Yu, Alex Ma, Jay Busch, M. Bolas, P. Debevec","doi":"10.1145/1837026.1837088","DOIUrl":null,"url":null,"abstract":"Head-mounted cameras are an increasingly important tool for capturing facial performances to drive virtual characters. They provide a fixed, unoccluded view of the face, useful for observing motion capture dots or as input to video analysis. However, the 2D imagery captured with these systems is typically affected by ambient light and generally fails to record subtle 3D shape changes as the face performs. We have developed a system that augments a head-mounted camera with LED-based photometric stereo. The system allows observation of the face independent of the ambient light and generates per-pixel surface normals so that the performance is recorded dynamically in 3D. The resulting data can be used for facial relighting or as better input to machine learning algorithms for driving an animated face.","PeriodicalId":167135,"journal":{"name":"2011 Conference for Visual Media Production","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Conference for Visual Media Production","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1837026.1837088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
Head-mounted cameras are an increasingly important tool for capturing facial performances to drive virtual characters. They provide a fixed, unoccluded view of the face, useful for observing motion capture dots or as input to video analysis. However, the 2D imagery captured with these systems is typically affected by ambient light and generally fails to record subtle 3D shape changes as the face performs. We have developed a system that augments a head-mounted camera with LED-based photometric stereo. The system allows observation of the face independent of the ambient light and generates per-pixel surface normals so that the performance is recorded dynamically in 3D. The resulting data can be used for facial relighting or as better input to machine learning algorithms for driving an animated face.