Research on adolescent emotion recognition based on visual information

Mingming Ji; Lifeng Han; Yuchao Yan; Xihui Zhang; Chen Yang; Zhenwei Han; Chenxin Dang

doi:10.1117/12.3038694

22 July 2024 Research on adolescent emotion recognition based on visual information

Mingming Ji, Lifeng Han, Yuchao Yan, Xihui Zhang, Chen Yang, Zhenwei Han, Chenxin Dang

Proceedings Volume 13222, International Conference on Signal Processing and Communication Security (ICSPCS 2024); 132220C (2024) https://doi.org/10.1117/12.3038694
Event: Third International Conference on Signal Processing and Communication Security (ICSPCS 2024), 2024, Chengdu, China

Abstract

Convolutional Neural Networks (CNN) are widely utilized in the field of computer vision, garnering particular attention in facial emotion recognition. Literature analysis indicates that attention mechanisms significantly enhance model precision and accuracy. However, existing facial emotion recognition models have not fully considered the interplay between convolutional neural networks and machine vision, nor the correlation between facial emotion recognition and the target user groups. This paper proposes a novel model, MD-CNN, which integrates convolutional neural networks with an attention mechanism and selects appropriate datasets based on the characteristics of the target groups. The model design includes an attention layer and experiments are conducted using the Affect Net dataset. Comparisons with other CNN emotion recognition models demonstrate that the proposed model significantly improves accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mingming Ji, Lifeng Han, Yuchao Yan, Xihui Zhang, Chen Yang, Zhenwei Han, and Chenxin Dang "Research on adolescent emotion recognition based on visual information", Proc. SPIE 13222, International Conference on Signal Processing and Communication Security (ICSPCS 2024), 132220C (22 July 2024); https://doi.org/10.1117/12.3038694

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