基于深度卷积网络的人脸表情识别

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI:10.1109/CISP-BMEI.2018.8633014

Minjun Wang, Zhihui Wang, Shaohui Zhang, J. Luan, Zezhong Jiao

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引用次数: 8

摘要

提出了一种基于深度体积和网络的人脸表情识别方法。该方法以面部表情图像作为CNN的输入，对CNN网络进行训练，然后利用训练好的网络进行面部表情识别。本文使用jaffe和ck+两个人脸表情库对算法进行验证，证明了算法的有效性，并表明其性能优于传统方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Face Expression Recognition Based on Deep Convolution Network

A method based on depth volume and network for facial expression recognition was proposed. This method takes the facial expression image as the input of the CNN and trains the CNN network, and then uses the trained network to perform facial expression recognition. This paper uses jaffe and ck+ two face expression libraries to verify the algorithm, proves the effectiveness of the algorithm, and shows that its performance is better than the traditional method.

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来源期刊

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

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