Author(s)

Dan Li^1,*, Jinping Sun^1,*, Weiwei Liu², Likai Wang²

Affiliation(s)

¹ School of Information Engineering(School of Big Data), Xuzhou University of Technology, Xuzhou, Jiangsu, China;

² Traffic police detachment of Xuzhou Public Security Bureau, Xuzhou Jiangsu, China.

Corresponding Author

Dan Li, email: lidanonline@xzit.edu.cn;

Jinping Sun, email: 313272361@qq.com

ABSTRACT

Due to the changes of expression, background, position and noise, the automatic recognition of facial expression image is a challenge for computer. The system uses the face detection module in OpenCV and Dlib library, loads 68 key point detection models to detect faces, and annotates the key points on the image. The Fer2013 database is trained to get the position information of 68 key points on the face. The expression set is predicted by the classifier, and the predicted probability is displayed visually.

KEYWORDS

Facial expression recognition; convolutional neural network; feature extraction; Tenserflow framework.

CITE THIS PAPER

Li Dan, Sun Jinping, Liu Weiwei, Wang Likai. Expression recognition system based on deep learning framework. Eurasia Journal of Science and Technology. 2022, 4(1): 35-42.

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