3D facial geometry analysis and estimation using embedded optical sensors on smart eyewear

Nao Asano, Yuta Sugiura, Katsutoshi Masai, Maki Sugimoto

研究成果: Conference contribution

抜粋

Facial performance capture is used for animation production that projects a performer's facial expression to a computer graphics model. Retro-reflective markers and cameras are widely used for the performance capture. To capture expressions, we need to place markers on the performer's face and calibrate the intrinsic and extrinsic parameters of cameras in advance. However, the measurable space is limited to the calibrated area. In this study, we propose a system to capture facial performance using a smart eyewear with photo-reflective sensors and machine learning technique. Also, we show a result of principal components analysis of facial geometry to determine a good estimation parameter set.

元の言語English
ホスト出版物のタイトルACM SIGGRAPH 2018 Posters, SIGGRAPH 2018
出版者Association for Computing Machinery, Inc
ISBN(印刷物)9781450358170
DOI
出版物ステータスPublished - 2018 8 12
イベントACM SIGGRAPH 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2018 - Vancouver, Canada
継続期間: 2018 8 122018 8 16

Other

OtherACM SIGGRAPH 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2018
Canada
Vancouver
期間18/8/1218/8/16

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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  • これを引用

    Asano, N., Sugiura, Y., Masai, K., & Sugimoto, M. (2018). 3D facial geometry analysis and estimation using embedded optical sensors on smart eyewear. : ACM SIGGRAPH 2018 Posters, SIGGRAPH 2018 [a45] Association for Computing Machinery, Inc. https://doi.org/10.1145/3230744.3230812