Facial expression recognition using temporal relations among facial movements

被引：0

作者：

Qiu, Yu ^{[1
]}

Zhao, Jie-Yu ^{[1
]}

Wang, Yan-Fang ^{[1
]}

机构：

[1] Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, Zhejiang

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2016年 / 44卷 / 06期

关键词：

Bayesian network; Facial expression recognition; Interval algebra; Sequential facial events;

D O I：

10.3969/j.issn.0372-2112.2016.06.007

中图分类号：

O144 [集合论]; O157 [组合数学（组合学）];

学科分类号：

070104 ;

摘要：

Spatial and temporal relations between different facial muscles are very important in the facial expression recognition process.However,these implicit relations have not been widely used due to the limitation of the current models.In order to make full use of spatial and temporal information,we model the facial expression as a complex activity consisting of different facial events.Furthermore,we introduce a special Bayesian network to capture the temporal relations among facial events and develop the corresponding algorithm for facial expression modeling and recognition.We only use the features based on tracking results and this method does not require the peak frames,which can improve the speed of training and recognition.Experimental results on the benchmark databases CK+ and MMI show that the proposed method is feasible in facial expression recognition and considerably improves the recognition accuracy. © 2016, Chinese Institute of Electronics. All right reserved.

引用

页码：1307 / 1313

页数：6

共 24 条

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