TY - GEN
T1 - Automatic facial expression recognition using SVM based on AAMs
AU - Wang, Li
AU - Li, Ruifeng
AU - Wang, Ke
PY - 2013
Y1 - 2013
N2 - An automatic facial expression recognition method is proposed to effectively recognize facial expression without any region unrelated to facial region. Support Vector Machine (SVM) is applied to recognize facial expression by Gabor features extracting using Gabor wavelet transformation after separate facial region from images Based on Active Appearance Models (AAMs), which reduce influence of illumination and pose. The feasibility and effectiveness of this system are verified by multiple experiments, and satisfied results are achieved.
AB - An automatic facial expression recognition method is proposed to effectively recognize facial expression without any region unrelated to facial region. Support Vector Machine (SVM) is applied to recognize facial expression by Gabor features extracting using Gabor wavelet transformation after separate facial region from images Based on Active Appearance Models (AAMs), which reduce influence of illumination and pose. The feasibility and effectiveness of this system are verified by multiple experiments, and satisfied results are achieved.
KW - Active Appearance Models
KW - Facial expression recognition
KW - Gabor feature
KW - Support Vector Machine
UR - http://www.scopus.com/inward/record.url?scp=84891848186&partnerID=8YFLogxK
U2 - 10.1109/IHMSC.2013.226
DO - 10.1109/IHMSC.2013.226
M3 - Conference contribution
AN - SCOPUS:84891848186
SN - 9780769550114
T3 - Proceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
SP - 330
EP - 333
BT - Proceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
T2 - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Y2 - 26 August 2013 through 27 August 2013
ER -