TY - GEN
T1 - Human emotion recognition based on active appearance model and semi-supervised fuzzy C-means
AU - Liliana, Dewi Yanti
AU - Widyanto, Muhammad Rahmat
AU - Basaruddin, T.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/3/6
Y1 - 2017/3/6
N2 - Human emotion recognition is an emerging research area in the field of social signal processing. Facial expression is an important means to detect human emotion. The problem is some facial expressions represent similar emotions. Thus, the recognition must consider the ambiguity in the way human expresses emotions through face. Existing methods do not take into account the level of expression's ambiguity. In our research, we specify face points and display the degree of fuzzy cluster on eight face emotions, namely anger, contempt, disgust, happy, surprise, sadness, fear, and neutral. The proposed methods are based on Active Appearance Model (AAM) and semi-supervised Fuzzy C-means (FCM). We tested the system on Cohn Kanade+ dataset of facial expression which provided eight classes of human emotion. Our methods gain an average accuracy rate of 80.71% and surpass the existing Fuzzy Inference System.
AB - Human emotion recognition is an emerging research area in the field of social signal processing. Facial expression is an important means to detect human emotion. The problem is some facial expressions represent similar emotions. Thus, the recognition must consider the ambiguity in the way human expresses emotions through face. Existing methods do not take into account the level of expression's ambiguity. In our research, we specify face points and display the degree of fuzzy cluster on eight face emotions, namely anger, contempt, disgust, happy, surprise, sadness, fear, and neutral. The proposed methods are based on Active Appearance Model (AAM) and semi-supervised Fuzzy C-means (FCM). We tested the system on Cohn Kanade+ dataset of facial expression which provided eight classes of human emotion. Our methods gain an average accuracy rate of 80.71% and surpass the existing Fuzzy Inference System.
KW - active appearance model
KW - facial expression recognition
KW - fuzzy c-means
KW - human emotion recognition
UR - http://www.scopus.com/inward/record.url?scp=85016996654&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2016.7872744
DO - 10.1109/ICACSIS.2016.7872744
M3 - Conference contribution
AN - SCOPUS:85016996654
T3 - 2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
SP - 439
EP - 445
BT - 2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
Y2 - 15 October 2016 through 16 October 2016
ER -