TY - GEN
T1 - Spontaneous facial expression recognition by heterogeneous convolutional networks
AU - Peng, Xianlin
AU - Li, Lei
AU - Feng, Xiaoyi
AU - Fan, Jianping
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Spontaneous facial expression achieves much attention recently as it has potential applications in the field of computer vision and pattern recognition. Although the convolutional networks have been applied for recognizing acted facial expressions and obtained the state-of-the-art performance, the performance of recognizing spontaneous facial expressions still needs to be improved. In this paper, a heterogeneous deep model is presented to recognize spontaneous expressions. The deep model consists of two types of convolutional networks with different architectures. To leverage the acted data, these two deep sub-networks are pre-trained over acted data and then transferred to the spontaneous data. Experiments have shown the advantages of the proposed method on the dataset of spontaneous facial expression.
AB - Spontaneous facial expression achieves much attention recently as it has potential applications in the field of computer vision and pattern recognition. Although the convolutional networks have been applied for recognizing acted facial expressions and obtained the state-of-the-art performance, the performance of recognizing spontaneous facial expressions still needs to be improved. In this paper, a heterogeneous deep model is presented to recognize spontaneous expressions. The deep model consists of two types of convolutional networks with different architectures. To leverage the acted data, these two deep sub-networks are pre-trained over acted data and then transferred to the spontaneous data. Experiments have shown the advantages of the proposed method on the dataset of spontaneous facial expression.
KW - Convolutional networks
KW - Deep learning
KW - Heterogeneous architecture
KW - Spontaneous facial expression
UR - https://www.scopus.com/pages/publications/85050200965
U2 - 10.1109/FADS.2017.8253196
DO - 10.1109/FADS.2017.8253196
M3 - 会议稿件
AN - SCOPUS:85050200965
T3 - Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017
SP - 70
EP - 73
BT - Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017
Y2 - 23 October 2017 through 25 October 2017
ER -