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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 3
903-910

Multimodal micro-expression recognition based on improved 3D ResNet18

Liang Yan
Huang Runcai
Lu Shicheng
School of Electrical & Electronic Engineering, Shanghai University of Engineering & Technology, Shanghai 201600, China
DOI: 10.19734/j.issn.1001-3695.2024.04.0216

Abstract

Addressing the challenges of temporal feature extraction in micro-expression recognition technology, including the difficulties in capturing due to their transience, the complexity of spatiotemporal information fusion, the overfitting problem caused by data sparsity, the limitations of static feature extraction methods, and the impact of data preprocessing on recognition performance, this paper proposed a multimodal micro-expression recognition method based on an improved 3D ResNet(IM3DR-MFER). By incorporating parameter reduction strategies and multi-scale context-aware fusion strategies into the traditional 3D ResNet network, it improved the 3D ResNet18, reducing parameters while enhancing the ability to capture facial local features and their information in a broad context. By integrating global facial features with optical flow dynamic features, it constructed a dual-modal input framework, significantly enhancing the models feature representation capabilities in different dimensions. By innovatively introducing a novel three-dimensional attention mechanism(CASANet), it adaptively identified and highlighted key features at each time point in the micro-expression sequence. Experimental results on CASME II, SAMM, and the composite dataset(CD) show that the proposed method achieves accuracy rates of 93.2%, 88.7%, and 84.6%, respectively, thereby verifying the effectiveness and advancement of the proposed method in facial micro-expression recognition tasks.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.04.0216
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 3
Section: Technology of Graphic & Image
Pages: 903-910
Serial Number: 1001-3695(2025)03-034-0903-08

Publish History

[2025-03-05] Printed Article

Cite This Article

梁岩, 黄润才, 卢士铖. 基于改进3D ResNet18的多模态微表情识别 [J]. 计算机应用研究, 2025, 42 (3): 903-910. (Liang Yan, Huang Runcai, Lu Shicheng. Multimodal micro-expression recognition based on improved 3D ResNet18 [J]. Application Research of Computers, 2025, 42 (3): 903-910. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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