Integration of global and local feature for face recognition

被引：15
|
作者：
Su Y. [1 ]
Shan S.-G. [2 ]
Chen X.-L. [2 ]
Gao W. [1 ,3 ]
机构：
[1] School of Computer Science and Technology, Harbin Institute of Technology
[2] Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, The Chinese Academy of Sciences
[3] Institute of Digital Media, Peking University
来源：
Ruan Jian Xue Bao/Journal of Software | 2010年 / 21卷 / 08期
关键词：
Classifier integration; Face recognition; Fourier transform; Gabor wavelet; Global feature; Local feature;
D O I：
10.3724/SP.J.1001.2010.03627
中图分类号：
学科分类号：
摘要：
This paper proposes to combine the global and local facial features in both serial and parallel manner. Firstly, global features are used for coarse classification. Then, global and local features are integrated for fine classification. In the proposed method, global and local features are extracted by Discrete Fourier Transform (DFT) and Gabor Wavelets Transform (GWT) respectively. Experiments on two large scale face databases (FERET and FRGC v2.0) validate that the proposed method can not only greatly increase the system accuracy but also improve the system speed. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码：1849 / 1862
页数：13
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