现代信息科技2024，Vol.8Issue(14)：26-29,36,5.DOI:10.19850/j.cnki.2096-4706.2024.14.006
基于对抗分解卷积网络的自发微表情种类判别
Discrimination of Spontaneous Micro-expression Types Based on Adversarial Decomposition Convolutional Network
吴俊1
作者信息
- 1. 抚州职业技术学院,江西 抚州 344000
- 折叠
摘要
Abstract
Aiming at the problems of the difficulty in extracting spontaneous micro-expression components and the low classification recognition accuracy,the adversarial decomposition convolutional network is proposed to realize the extraction and classification of spontaneous micro-expression components through game and cooperation between networks.The images of neutral face are used as the real samples of the discriminant network,and images of spontaneous micro-expression are used as inputting samples of the decomposition network.According to the adversary between networks,output images containing only spontaneous micro-expression components can be obtained.Then,transfer learning and classification of spontaneous micro-expression components are realized through the transfer network.The cross database experimental results of spontaneous micro-expression show that the classification accuracy is improved and it has the effect of overcoming the differences of race and skin color in different databases.关键词
自发微表情/分类/分解/对抗生成网络Key words
spontaneous micro-expression/classification/decomposition/Generative Adversarial Networks分类
信息技术与安全科学引用本文复制引用
吴俊..基于对抗分解卷积网络的自发微表情种类判别[J].现代信息科技,2024,8(14):26-29,36,5.
