Title: Facial feature localisation and subtle expression recognition based on deep convolution neural network

Authors: Qiaojun Li; Peipei Wang

Addresses: Department of Electronic Information Engineering, Henan Polytechnic Institute, Nanyang, 473000, China ' Department of Electronic Information Engineering, Henan Polytechnic Institute, Nanyang, 473000, China

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.

Keywords: deep convolution; neural network; facial feature localisation; subtle expression; recognition.

DOI: 10.1504/IJBM.2022.124671

International Journal of Biometrics, 2022 Vol.14 No.3/4, pp.268 - 284

Received: 15 Jul 2020
Accepted: 08 Sep 2020
Published online: 05 Aug 2022 *

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