自动化学报2024，Vol.50Issue(7)：1445-1457,13.DOI:10.16383/j.aas.c230641
基于多层级信息融合网络的微表情识别方法
A Micro-expression Recognition Method Based on Multi-level Information Fusion Network
摘要
Abstract
Micro-expressions are subtle and involuntary changes during emotional expression.Accurate and effi-cient recognition of these is crucial for the early diagnosis and treatment of mental illnesses.Most of the existing methods often neglect the connections between key facial areas in micro-expressions,making it difficult to capture the subtle changes in small sample image spaces,resulting in low recognition rates.To address this,a micro-expres-sion recognition method is proposed based on a multi-level information fusion network.This method includes a video frame selection strategy based on frequency amplitude,which can select frames with high-intensity expres-sions from micro-expression videos.Additionally,this method includes a multi-level information extraction network using self-attention mechanisms and graph convolutional networks,and a fusion network that incorporates global image information,which can capture the subtle changes of facial micro-expressions from different levels to improve the recognition of specific categories.Experiments on public datasets show that our method effectively improves the accuracy and outperforms other advanced methods.关键词
微表情识别/深度学习/图卷积网络/多层级融合Key words
Micro-expression recognition/deep learning/graph convolutional network/multi-level fusion引用本文复制引用
陈妍,吴乐晨,王聪..基于多层级信息融合网络的微表情识别方法[J].自动化学报,2024,50(7):1445-1457,13.基金项目
国家自然科学基金(62273140,72342018)资助Supported by National Natural Science Foundation of China(62273140,72342018) （62273140,72342018）
