Facial Expression Recognition Based on Multi-dataset Neural Network
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Facial activity is the most powerful and natural means for understanding emotional expression for humans. Recent years, extensive efforts have been devoted to facial expression recognition by using neural networks. However, automated emotion recognition in the wild from facial images remains a challenging problem. In this paper, an effective facial expression recognition scheme is proposed. A multi-dataset neural network is developed to learn facial expression features in several different but related datasets. The novel multi-dataset network fuses the intermediate layers of a deep convolutional neural network (CNN) by using separate CNNs and a multi-dataset loss function. Experimental results performed on emotion database demonstrate that our proposed method outperforms state-of-the-art.
KeywordsFacial expression recognition, design of network architecture, deep learning, human–computer interaction, convolutional neural network
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2020 vol. 29, č. 1, s. 259-266. ISSN 1210-2512
- 2020/1