Enhanced Facial Emotion Recognition Using Deep Learning Techniques: A Multi-Stage Approach

DOI

10.2991/978-94-6463-512-6_53How to use a DOI?

Keywords

Facial Emotion Recognition; Deep Learning; Convolutional Neural Network; Attention Mechanism

Abstract

This research introduces a cutting-edge facial emotion recognition (FER) system that leverages deep learning methods to significantly enhance the precision and resilience of detecting emotions from facial expressions. The proposed approach utilizes a meticulously optimized convolutional neural network (CNN) for effective feature extraction, enhanced by an attention mechanism that focuses on relevant facial regions, and incorporates comprehensive data augmentation techniques. Extensive experiments conducted on the FER 2013 dataset demonstrate significant improvements in accuracy, especially in recognizing spontaneous and subtle expressions. The results show that the model effectively handles diverse facial emotions, with notable performance in categories such as happiness and surprise. The practical implications of this research are significant, enhancing human-computer interaction, improving security systems, and providing valuable insights for psychological research and therapy. Future research will aim to enhance the model's robustness across various datasets and real-world conditions by exploring additional data augmentation techniques, optimizing hyperparameters, and incorporating more sophisticated attention mechanisms. This study propels the field of FER technology forward, aiding in the creation of more intuitive and efficient human-computer interfaces.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nuoya Liu
PY  - 2024
DA  - 2024/09/23
TI  - Enhanced Facial Emotion Recognition Using Deep Learning Techniques: A Multi-Stage Approach
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
PB  - Atlantis Press
SP  - 502
EP  - 511
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-512-6_53
DO  - 10.2991/978-94-6463-512-6_53
ID  - Liu2024
ER  -