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
收藏
页码：724 / 731
页数：8
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