TY - GEN
T1 - Affective wear
T2 - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2015
AU - Masai, Katsutoshi
AU - Sugiura, Yuta
AU - Ogata, Masa
AU - Suzuki, Katsuhiro
AU - Nakamura, Fumihiko
AU - Shimamura, Sho
AU - Kunze, Kai
AU - Inami, Masahiko
AU - Sugimoto, Maki
PY - 2015/7/31
Y1 - 2015/7/31
N2 - Facial expression is a powerful way for us to exchange information nonverbally. They can give us insights into how people feel and think. There are a number of works related to facial expression detection in computer vision. However, most works focus on camera-based systems installed in the environment. With this method, it is difficult to track user's face if user moves constantly. Moreover, user's facial expression can be recognized at only a limited place. We present the eyewear that can detect facial expression anytime, anywhere (Figure 1 a). This eyewear can categorize 7 facial expressions by measuring the distance between an eyewear frame and a skin surface of a person's face with 8 photo reflective sensors. Recognizable states are as follows: neutral, smile, laugh, disgust, angry, sad and surprise. With our method, an individual difference can be ignored with user-dependent training. Several works show the wearable systems that can recognize facial expression. Yet, these works focus on detecting only one specific facial expression. Our contribution is detecting 7 facial expression states in daily life. With our device, user can better understand their mind, and computing systems can tap into the rich set of information provided by nonverbal communication.
AB - Facial expression is a powerful way for us to exchange information nonverbally. They can give us insights into how people feel and think. There are a number of works related to facial expression detection in computer vision. However, most works focus on camera-based systems installed in the environment. With this method, it is difficult to track user's face if user moves constantly. Moreover, user's facial expression can be recognized at only a limited place. We present the eyewear that can detect facial expression anytime, anywhere (Figure 1 a). This eyewear can categorize 7 facial expressions by measuring the distance between an eyewear frame and a skin surface of a person's face with 8 photo reflective sensors. Recognizable states are as follows: neutral, smile, laugh, disgust, angry, sad and surprise. With our method, an individual difference can be ignored with user-dependent training. Several works show the wearable systems that can recognize facial expression. Yet, these works focus on detecting only one specific facial expression. Our contribution is detecting 7 facial expression states in daily life. With our device, user can better understand their mind, and computing systems can tap into the rich set of information provided by nonverbal communication.
UR - http://www.scopus.com/inward/record.url?scp=84959331782&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959331782&partnerID=8YFLogxK
U2 - 10.1145/2787626.2792632
DO - 10.1145/2787626.2792632
M3 - Conference contribution
AN - SCOPUS:84959331782
T3 - ACM SIGGRAPH 2015 Posters, SIGGRAPH 2015
BT - ACM SIGGRAPH 2015 Posters, SIGGRAPH 2015
PB - Association for Computing Machinery, Inc
Y2 - 9 August 2015 through 13 August 2015
ER -