TY - GEN
T1 - 3D facial geometry analysis and estimation using embedded optical sensors on smart eyewear
AU - Asano, Nao
AU - Sugiura, Yuta
AU - Masai, Katsutoshi
AU - Sugimoto, Maki
N1 - Funding Information:
This research was partially supported by JST CREST (JPMJCR14E1) and JSPS KAKENHI (16H05870).
Publisher Copyright:
© 2018 Copyright held by the owner/author(s).
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/8/12
Y1 - 2018/8/12
N2 - 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.
AB - 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.
KW - Facial Performance Capture
KW - Wearable Device
UR - http://www.scopus.com/inward/record.url?scp=85054815733&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054815733&partnerID=8YFLogxK
U2 - 10.1145/3230744.3230812
DO - 10.1145/3230744.3230812
M3 - Conference contribution
AN - SCOPUS:85054815733
SN - 9781450358170
T3 - ACM SIGGRAPH 2018 Posters, SIGGRAPH 2018
BT - ACM SIGGRAPH 2018 Posters, SIGGRAPH 2018
PB - Association for Computing Machinery, Inc
T2 - ACM SIGGRAPH 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2018
Y2 - 12 August 2018 through 16 August 2018
ER -