Facial Emotion Detection Using Deep Learning

Akriti Jaiswal · A. Krishnama Raju · Suman Deb

219 citations0/0 files storedInternational Conference for Emerging Technology (INCET)

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

Abstract

Human Emotion detection from image is one of the most powerful and challenging research task in social communication. Deep learning (DL) based emotion detection gives performance better than traditional methods with image processing. This paper presents the design of an artificial intelligence (AI) system capable of emotion detection through facial expressions. It discusses about the procedure of emotion detection, which includes basically three main steps: face detection, features extraction, and emotion classification. This paper proposed a convolutional neural networks (CNN) based deep learning architecture for emotion detection from images. The performance of the proposed method is evaluated using two datasets Facial emotion recognition challenge (FERC-2013) and Japaness female facial emotion (JAFFE). The accuracies achieved with proposed model are 70.14 and 98.65 percentage for FERC-2013 and JAFFE datasets respectively.

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References

1872The expression of the emotions in man and animals.1971Constants across cultures in the face and emotion.2010The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression 2020Deep Facial Expression Recognition: A Survey 2000Emotion Recognition in Speech Using Neural Networks

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