Facial Expression Recognition Based on Multi-Feature Fusion and HOSVD

被引:0
|
作者
He, Ying [1 ]
He, Xiaoju [2 ]
机构
[1] Tianjin Univ, Renai Coll, Dept Comp Sci & Technol, Tianjin, Peoples R China
[2] Anyang Univ, Sch Aviat Engn, Anyang, Henan, Peoples R China
来源
PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年
关键词
expression recognition; expression feature extraction; tensor analysis; high-order singular value decomposition;
D O I
10.1109/itnec.2019.8729003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To the problem of low recognition rate for human-independent facial expression, this paper proposed a facial expression recognition algorithm based on geometric and texture fusion features and HOSVD(High-Order Singular Value Decomposition). The algorithm transforms the facial expression recognition problem into the tensor domain, and extracts human-independent expression features using HOSVD. Then the interference caused by individual face differences on expression recognition is effectively excluded. The algorithm was tested on the Japanese Female Facial Expression database, and the results showed that the method achieved better recognition rate in human-independent experiments.
引用
收藏
页码:638 / 643
页数:6
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