Facial feature localisation and subtle expression recognition based on deep convolution neural network
by Qiaojun Li; Peipei Wang
International Journal of Biometrics (IJBM), Vol. 14, No. 3/4, 2022

Abstract: In order to solve the problems existing in traditional face recognition methods, such as low accuracy of face feature location, poor accuracy of subtle expression recognition and long recognition time, a face feature localisation and subtle expression recognition based on deep convolution neural network is proposed. The principle of deep convolution neural network is analysed, and the feature extraction of human face is placed in convolution layer and pooling layer. The foreground and background entropy of face image are obtained by binarisation method of face image. Optical flow characteristics of all positions of frame image are obtained by using deep convolution neural network, and the recognition of facial subtle expression is completed. The experimental results show that the accuracy of the proposed method is up to 98%, the recognition accuracy of facial expression is high, and the recognition time is short.

Online publication date: Fri, 05-Aug-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com