Classification of facial images using Gaussian mixture models

被引：0

作者：

Liao, P ^{[1
]}

Gao, W

Shen, L

Chen, XL

Shan, SG

Zeng, WB

机构：

[1] Chinese Acad Sci, ICT, YCNC, FRTJDL, Beijing 100080, Peoples R China

[2] Chinese Acad Sci, Comp Technol Inst, Beijing 100080, Peoples R China

[3] Harbin Inst Technol, Dept Comp Sci, Harbin 150001, Peoples R China

[4] YCNC Co, Chengdu 610016, SiChuan, Peoples R China

来源：

ADVANCES IN MUTLIMEDIA INFORMATION PROCESSING - PCM 2001, PROCEEDINGS | 2001年 / 2195卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a new technique for face recognition, Two distinct and mutually exclusive classes of difference between two facial images are defined: within-class differences set (differences in appearance of the same individual) and between-class diffierences set (differences in appearance between different individuals). Then Gaussian mixture models (GMMs) are used to estimate the eigenspace densities of the two classes. And subsequently a matching similarity measure is computed based on the maximum likelihood (ML) method. The new method achieved as much as 45% error reduction compared to the standard eigenface approach on the ORL database.

引用

页码：724 / 731

页数：8

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