Title: Facial expression recognition method based on multi-level feature fusion of high-resolution images

Authors: Li Wan; Wenzhi Cheng

Addresses: School of Information Engineering, Hunan University of Science and Engineering, Hunan, 425199, China ' School of Information Engineering, Hunan University of Science and Engineering, Hunan, 425199, China

Abstract: To improve the accuracy of facial expression recognition, the paper designs a facial expression recognition method based on multi-level feature fusion of high-resolution images. Firstly, smooth the noise and texture in the facial image and perform enhancement processing. Secondly, extract multi-level features of facial images, and then fuse multi-level features through reverse solving. Thirdly, extract the attributes of different regions of the face and assign them to the corresponding representation data. Then, extract decoupled data of facial expressions based on feature fusion results. Lastly, compare decoupled representation and representation data to complete the facial expression recognition. The experiment shows that the geometric mean of the recognition results obtained by this method is between 0.963 and 0.989, and the similarity of the feature vectors is between 0.972 and 0.988, indicating that this method can accurately output facial expression recognition results.

Keywords: facial images; expression recognition; high-resolution images; multi-level feature fusion.

DOI: 10.1504/IJBM.2025.143718

International Journal of Biometrics, 2025 Vol.17 No.1/2, pp.57 - 72

Received: 09 Nov 2023
Accepted: 30 Dec 2023
Published online: 06 Jan 2025 *

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