TY - GEN
T1 - AffectiveHMD
T2 - ACM SIGGRAPH 2019 Emerging Technologies - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2019
AU - Murakami, Masaaki
AU - Kikui, Kosuke
AU - Suzuki, Katsuhiro
AU - Nakamura, Fumihiko
AU - Fukuoka, Masaaki
AU - Masai, Katsutoshi
AU - Sugiura, Yuta
AU - Sugimoto, Maki
N1 - Funding Information:
This work was supported by JSPS KAKENHI (16H05870) and JST ERATO (JPMJER1701).
Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/7/28
Y1 - 2019/7/28
N2 - We propose a facial expression mapping technology between virtual avatars and Head-Mounted Display (HMD) users. HMDs allow people to enjoy an immersive Virtual Reality (VR) experience. A virtual avatar can be a representative of the user in the virtual environment. However, the synchronization of the virtual avatar’s expressions with those of the HMD user is limited. The major problem of wearing an HMD is that a large portion of the user’s face is occluded, making facial recognition difficult in an HMD-based virtual environment. To overcome this problem, we propose a facial expression mapping technology using photo-reflective sensors. The sensors attached inside the HMD measure the reflection intensity between the sensors and the user’s face. The intensity values of five basic facial expressions (Neutral, Happy, Angry, Surprised, and Sad) are used for training a classifier to estimate the facial expression of a user. In Siggraph 2019, the user can enjoy two application, the facial expression synchronization with the avatar, and simple manipulation experience for a virtual environment by facial expressions.
AB - We propose a facial expression mapping technology between virtual avatars and Head-Mounted Display (HMD) users. HMDs allow people to enjoy an immersive Virtual Reality (VR) experience. A virtual avatar can be a representative of the user in the virtual environment. However, the synchronization of the virtual avatar’s expressions with those of the HMD user is limited. The major problem of wearing an HMD is that a large portion of the user’s face is occluded, making facial recognition difficult in an HMD-based virtual environment. To overcome this problem, we propose a facial expression mapping technology using photo-reflective sensors. The sensors attached inside the HMD measure the reflection intensity between the sensors and the user’s face. The intensity values of five basic facial expressions (Neutral, Happy, Angry, Surprised, and Sad) are used for training a classifier to estimate the facial expression of a user. In Siggraph 2019, the user can enjoy two application, the facial expression synchronization with the avatar, and simple manipulation experience for a virtual environment by facial expressions.
KW - Avatar
KW - Classification
KW - Facial expression recognition
UR - http://www.scopus.com/inward/record.url?scp=85083952853&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85083952853&partnerID=8YFLogxK
U2 - 10.1145/3305367.3335039
DO - 10.1145/3305367.3335039
M3 - Conference contribution
AN - SCOPUS:85083952853
T3 - ACM SIGGRAPH 2019 Emerging Technologies, SIGGRAPH 2019
BT - ACM SIGGRAPH 2019 Emerging Technologies, SIGGRAPH 2019
PB - Association for Computing Machinery, Inc
Y2 - 28 July 2019
ER -