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Facial Expression Recognition Based on Random Forest and Convolutional Neural Network

1
School of Control Science and Engineering, Shandong University, Jinan 250061, China
2
School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, China
*
Author to whom correspondence should be addressed.
Information 2019, 10(12), 375; https://doi.org/10.3390/info10120375
Received: 27 October 2019 / Revised: 19 November 2019 / Accepted: 25 November 2019 / Published: 28 November 2019
As an important part of emotion research, facial expression recognition is a necessary requirement in human–machine interface. Generally, a face expression recognition system includes face detection, feature extraction, and feature classification. Although great success has been made by the traditional machine learning methods, most of them have complex computational problems and lack the ability to extract comprehensive and abstract features. Deep learning-based methods can realize a higher recognition rate for facial expressions, but a large number of training samples and tuning parameters are needed, and the hardware requirement is very high. For the above problems, this paper proposes a method combining features that extracted by the convolutional neural network (CNN) with the C4.5 classifier to recognize facial expressions, which not only can address the incompleteness of handcrafted features but also can avoid the high hardware configuration in the deep learning model. Considering some problems of overfitting and weak generalization ability of the single classifier, random forest is applied in this paper. Meanwhile, this paper makes some improvements for C4.5 classifier and the traditional random forest in the process of experiments. A large number of experiments have proved the effectiveness and feasibility of the proposed method. View Full-Text
Keywords: facial expression recognition; feature extraction; convolutional neural network; random forest facial expression recognition; feature extraction; convolutional neural network; random forest
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Wang, Y.; Li, Y.; Song, Y.; Rong, X. Facial Expression Recognition Based on Random Forest and Convolutional Neural Network. Information 2019, 10, 375.

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