Automatic Facial Expression Recognition Using DCNN

Veena Mayya · Radhika M. Pai · M. M. Manohara Pai

126 citations0/0 files storedProcedia Computer Science

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

Abstract

Face depicts a wide range of information about identity, age, sex, race as well as emotional and mental state. Facial expressions play crucial role in social interactions and commonly used in the behavioral interpretation of emotions. Automatic facial expression recognition is one of the interesting and challenging problem in computer vision due to its potential applications such as Human Computer Interaction(HCI), behavioral science, video games etc. In this paper, a novel method for automatically recognizing facial expressions using Deep Convolutional Neural Network(DCNN) features is proposed. The proposed model focuses on recognizing the facial expressions of an individual from a single image. The feature extraction time is significantly reduced due to the usage of general purpose graphic processing unit (GPGPU). From an evaluation on two publicly available facial expression datasets, we have found that using DCNN features, we can achieve the state-of-the-art recognition rate.

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References

1977The Measurement of Observer Agreement for Categorical Data 1978Facial Action Coding System 2010The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression 2011The computer expression recognition toolbox (CERT)2005Facial Expression Analysis 2011Facial Expression Recognition Using Facial Movement Features 2016Hierarchical committee of deep convolutional neural networks for robust facial expression recognition

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2022Facial Emotion Expressions in Human–Robot Interaction: A Survey 2018Integrating Deep and Shallow Models for Multi-Modal Depression Analysis—Hybrid Architectures 2017Supervised Committee of Convolutional Neural Networks in Automated Facial Expression Analysis 2019CNN and LSTM Based Facial Expression Analysis Model for a Humanoid Robot 2020Facial Expressions Recognition for Human–Robot Interaction Using Deep Convolutional Neural Networks with Rectified Adam Optimizer 20193D Approaches and Challenges in Facial Expression Recognition Algorithms—A Literature Review

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