Recognition of facial expressions based on CNN features
Autor: | Luis Pellegrin, Hugo Jair Escalante, Sonia M. González-Lozoya, Ma. Auxilio Medina, Jorge de la Calleja, Antonio Benitez-Ruiz |
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Rok vydání: | 2020 |
Předmět: |
Facial expression
Computer Networks and Communications Computer science business.industry Generalization Feature vector 020207 software engineering Pattern recognition 02 engineering and technology Convolutional neural network Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Media Technology Artificial intelligence business Software |
Zdroj: | Multimedia Tools and Applications. 79:13987-14007 |
ISSN: | 1573-7721 1380-7501 |
DOI: | 10.1007/s11042-020-08681-4 |
Popis: | Facial expressions are a natural way to communicate emotional states and intentions. In recent years, automatic facial expression recognition (FER) has been studied due to its practical importance in many human-behavior analysis tasks such as interviews, autonomous-driving, medical treatment, among others. In this paper we propose a method for facial expression recognition based on features extracted with convolutional neural networks (CNN), taking advantage of a pre-trained model in similar tasks. Unlike other approaches, the proposed FER method learns from mixed instances taken from different databases with the goal of improving generalization, a major issue in machine learning. Experimental results show that the FER method is able to recognize the six universal expressions with an accuracy above 92% considering five of the widely used databases. In addition, we have extended our method to deal with micro-expressions recognition (MER). In this regard, we propose three strategies to create a temporal-aggregated feature vector: mean, standard deviation and early fusion. In this case, the best result is 78.80% accuracy. Furthermore, we present a prototype system that implements the two proposed methods for FER and MER as a tool that allows to analyze videos. |
Databáze: | OpenAIRE |
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