TY - GEN
T1 - Facial expression recognition in video sequences
AU - Tai, Shen-Chuan
AU - Huang, Hungfu
PY - 2009/9/10
Y1 - 2009/9/10
N2 - This paper proposes asystem forthe facial expression recognition. Firstly, we perform noise reduction by a median filter of facial expression image. Then, a cross-correlation of optical flow and mathematical models from the facial points are used. To define these facial points of interest in the first frame of an input face sequence image, which utilize manually marker. The facial points were automatically tracked by a cross-correlation, which is based on optical flow,and then extracted the feature vectors. The mathematical model extracts features from the feature vectors. An ELMAN neural network was applied to classify expressions. The performances of the proposed facial expressions recognition were computed by Cohn-Kanade facial expressions database. This proposed approach achieved a high recognition rate.
AB - This paper proposes asystem forthe facial expression recognition. Firstly, we perform noise reduction by a median filter of facial expression image. Then, a cross-correlation of optical flow and mathematical models from the facial points are used. To define these facial points of interest in the first frame of an input face sequence image, which utilize manually marker. The facial points were automatically tracked by a cross-correlation, which is based on optical flow,and then extracted the feature vectors. The mathematical model extracts features from the feature vectors. An ELMAN neural network was applied to classify expressions. The performances of the proposed facial expressions recognition were computed by Cohn-Kanade facial expressions database. This proposed approach achieved a high recognition rate.
UR - http://www.scopus.com/inward/record.url?scp=69849108067&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=69849108067&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-01513-7_113
DO - 10.1007/978-3-642-01513-7_113
M3 - Conference contribution
AN - SCOPUS:69849108067
SN - 3642015123
SN - 9783642015120
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1026
EP - 1033
BT - Advances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings
T2 - 6th International Symposium on Neural Networks, ISNN 2009
Y2 - 26 May 2009 through 29 May 2009
ER -