计算机工程2024，Vol.50Issue(5)：241-249,9.DOI:10.19678/j.issn.1000-3428.0067538
基于关键区域遮挡与重建的人脸表情识别
Facial Expression Recognition Based on Key Region Masking and Reconstruction
摘要
Abstract
To overcome the negative impact of irrelevant information interference and masking issues on the performance of facial expression recognition in the wild,this study proposes a facial expression recognition model based on key region masking and reconstruction.A multi-scale feature extraction network is first used to extract global features from facial images.Thereafter,the features of key regions,based on 68 facial landmarks,are extracted and encoded with attention mechanisms to learn prior relationships between the features of the key regions.To further enhance the discriminative capability of the extracted features for improved recognition performance,a key region masking and reconstruction module is designed based on self-supervised learning.This module aims to reconstruct randomly masked features of key regions using known region information.Extensive experiments are conducted to validate the generalization ability of the model,and ablation experiments confirm the effectiveness of each module in the model.The experimental results demonstrate that the model achieves recognition accuracies of 88.44％and 86.09％on the Real-world Affective Faces DataBase(RAF-DB)and the Occlusion-RAF-DB dataset,respectively,effectively improving the performance of facial expression recognition in natural scenarios compared to models such as Vision Transformer(ViT).关键词
人脸表情识别/多尺度关键区域特征/注意力机制/自监督学习/遮挡与重建Key words
facial expression recognition/multiscale key region feature/attention mechanism/self-supervised learning/masking and reconstruction分类
信息技术与安全科学引用本文复制引用
李晶,李健,陈海丰,张倩,王丽燕,裴二成..基于关键区域遮挡与重建的人脸表情识别[J].计算机工程,2024,50(5):241-249,9.基金项目
国家自然科学基金(62306172) （62306172）
国家土建结构预制装配化工程技术研究中心沈祖炎专项基金(2019CPCCE-K02) （2019CPCCE-K02）
陕西省自然科学基础研究计划项目(2022JQ-662) （2022JQ-662）
2021年陕西科技大学教育信息化教学改革研究项目(JXJG2021-09) （JXJG2021-09）
陕西科技大学博士科研启动基金(126022325). （126022325）
