A-MobileNet: An approach of facial expression recognition

Alexandria Engineering Journal

Haoming Zhang¹  Jianguo Ju²  Bo Wang³  Qingyi Hua³  Yahui Nan³ 

[1] Corresponding author.;Department of Computer Science and Technology, Lvliang University, Lvliang 033000, China;School of Information Science and Technology, Northwest University, Xi'an 710027, China;

关键词: Attention module;    Center loss;    Facial expression recognition;    Channel attention;    Spatial attention;   

DOI  :  

来源: DOAJ

【 摘 要 】

Facial expression recognition (FER) is to separate the specific expression state from the given static image or video to determine the psychological emotions of the recognized object, the realization of the computer's understanding and recognition of facial expressions have fundamentally changed the relationship between human and computer, to achieve better human computer interaction (HCI). In recent years, FER has attracted widespread attention in the fields of HCI, security, communications and driving, and has become one of the research hotspots. In the mobile Internet era, the need for lightweight networking and real-time performance is growing. In this paper, a lightweight A-MobileNet model is proposed. First, the attention module is introduced into the MobileNetV1 model to enhance the local feature extraction of facial expressions. Then, the center loss and softmax loss are combined to optimize the model parameters to reduce intra-class distance and increase inter-class distance. Compared with the original MobileNet series models, our method significantly improves recognition accuracy without increasing the number of model parameters. Compared with others, A- MobileNet model achieves better results on the FERPlus and RAF-DB datasets.

【 授权许可】

Unknown