The Extensive Usage of the Facial Image Threshing Machine for Facial Emotion Recognition Performance

Jung Hwan Kim · Alwin Poulose · Dong Seog Han

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Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Abstract

Facial emotion recognition (FER) systems play a significant role in identifying driver emotions. Accurate facial emotion recognition of drivers in autonomous vehicles reduces road rage. However, training even the advanced FER model without proper datasets causes poor performance in real-time testing. FER system performance is heavily affected by the quality of datasets than the quality of the algorithms. To improve FER system performance for autonomous vehicles, we propose a facial image threshing (FIT) machine that uses advanced features of pre-trained facial recognition and training from the Xception algorithm. The FIT machine involved removing irrelevant facial images, collecting facial images, correcting misplacing face data, and merging original datasets on a massive scale, in addition to the data-augmentation technique. The final FER results of the proposed method improved the validation accuracy by 16.95% over the conventional approach with the FER 2013 dataset. The confusion matrix evaluation based on the unseen private dataset shows a 5% improvement over the original approach with the FER 2013 dataset to confirm the real-time testing.

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References

2010The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression 2020Deep Facial Expression Recognition: A Survey 2017Self-report captures 27 distinct categories of emotion bridged by continuous gradients 2019Efficient Facial Expression Recognition Algorithm Based on Hierarchical Deep Neural Network Structure 2013Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"2020The Facial Emotion Recognition (FER-2013) Dataset for Prediction System of Micro-Expressions Face Using the Convolutional Neural Network (CNN) Algorithm based Raspberry Pi

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2023New Trends in Emotion Recognition Using Image Analysis by Neural Networks, a Systematic Review 2023Role of Zoning in Facial Expression Using Deep Learning 2023Hybrid Facial Emotion Recognition Using CNN-Based Features 2021Leaderboard Positions and Stress—Experimental Investigations into an Element of Gamification

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