Facial expression recognition based on FB2DPCA and multi-classifier fusion

被引：1

作者：

Hua, Bin ^{[1
]}

Liu, Ting ^{[1
]}

机构：

[1] Tianjin Univ Finance & Econ, Inst Technol, Tianjin, Peoples R China

来源：

ICIC 2009: SECOND INTERNATIONAL CONFERENCE ON INFORMATION AND COMPUTING SCIENCE, VOL 2, PROCEEDINGS: IMAGE ANALYSIS, INFORMATION AND SIGNAL PROCESSING | 2009年

关键词：

facial expression recognition; FB2DPCA; multi-classifier fusion; feature extraction;

D O I：

10.1109/ICIC.2009.200

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A method of feature block two-dimensional principal component analysis (FB2DPCA) and multi-classifier combination is proposed for facial expression recognition. First, FB2DPCA is applied to extract human facial expression features, and then the expression classified result is obtained based on multi-classifier fusion with fuzzy integral. This proposed method is validated through the results of experiments on JAFFE facial expression database, and a high recognition rate is also achieved.

引用

页码：353 / 356

页数：4

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