A 3D CNN Model With 3d CBAM Layer For Micro-Expression Recognition
Authors: 
Boyu Xiao, Shujun Chen, Jiahao Wen, Xudong Liu, Yuchen Wang, Kai Shi, Shuangxi LiAuthors Info & Claims
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Abstract
Facial microexpression recognition in videos is a popular area of computer vision research. Microexpressions are non-verbal expressions of human emotions that often appear when people try to hide or control their emotions.There are many facial expression recognition methods in related fields, but micro-expression recognition in videos has not been accurate enough. This paper aims to study micro-expression recognition technology, which can effectively identify small and short-lived expression changes on human faces. This study proposes a micro-expression recognition method based on computer vision and machine learning by analyzing facial features and spatio-temporal feature extraction. First, we collected a video dataset containing micro-expressions and performed preprocessing and feature extraction on them. Then, we use more advanced methods in the field and methods proposed by the team to train and test the model to recognize multiple micro-expression categories. Experimental results show that our method achieves higher accuracy and more stable performance in micro-expression recognition tasks.
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Published In
December 2023
467 pages
ISBN:9798400716966
DOI:10.1145/3661638
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 01 June 2024
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AISNS 2023
AISNS 2023: 2023 International Conference on Artificial Intelligence, Systems and Network Security
December 22 - 24, 2023
Mianyang, China
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