Facial Expression Recognition with Convolutional Neural Networks

Shekhar Singh · Fatma Nasoz

136 citations0/0 files storedIEEE Annual Computing and Communication Workshop and Conference (CCWC)

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

Abstract

Emotions are a powerful tool in communication and one way that humans show their emotions is through their facial expressions. One of the challenging and powerful tasks in social communications is facial expression recognition, as in non-verbal communication, facial expressions are key. In the field of Artificial Intelligence, Facial Expression Recognition (FER) is an active research area, with several recent studies using Convolutional Neural Networks (CNNs). In this paper, we demonstrate the classification of FER based on static images, using CNNs, without requiring any pre-processing or feature extraction tasks. The paper also illustrates techniques to improve future accuracy in this area by using pre-processing, which includes face detection and illumination correction. Feature extraction is used to extract the most prominent parts of the face, including the jaw, mouth, eyes, nose, and eyebrows. Furthermore, we also discuss the literature review and present our CNN architecture, and the challenges of using max-pooling and dropout, which eventually aided in better performance. We obtained a test accuracy of 61.7% on FER2013 in a seven-classes classification task compared to 75.2% in state-of-the-art classification.

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References

1872The expression of the emotions in man and animals.2016Facial expression recognition with Convolutional Neural Networks: Coping with few data and the training sample order 2016Facial Expression Recognition using Convolutional Neural Networks: State of the Art

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2024Advances in Facial Expression Recognition: A Survey of Methods, Benchmarks, Models, and Datasets 2019Real Time Emotion Recognition from Facial Expressions Using CNN Architecture 2022Four-layer ConvNet to facial emotion recognition with minimal epochs and the significance of data diversity 2021Facial Emotion Recognition using Convolution Neural Network 2017Deep Convolutional Neural Network for Facial Expression Recognition Using Facial Parts 2017Stacked deep convolutional auto-encoders for emotion recognition from facial expressions 2019Human Emotion Recognition using Convolutional Neural Network in Real Time 2021Human Facial Emotion Detection Using Deep Learning

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