Dynamically Optimizing Face Recognition Using PCA

被引：0
|
作者：
Zhao, Zhihong [1 ]
Li, Beibei [2 ]
机构：
[1] Nanjing Inst Ind Technol, Elect & Automat Dept, Nanjing, Jiangsu, Peoples R China
[2] Shanghai Second Polytech Univ, Sch Elect & Elect Engn, Shanghai, Peoples R China
来源：
FOURTH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (CCAIS 2015) | 2015年
关键词：
face recognition; principle component analysis; Eigenvalue; SAMPLE;
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：
A dynamically optimizing PCA method for face recognition is presented. Firstly, DCT is adopted, and their mean gray values are obtained. The face images are grouped into three sorted groups: Large, Medium and Small, and then calculate their means. Then, the Eigenvalue number is chosen as 9 and 10. Finally, recognition and reconstruction may be accomplished. The results show that this method achieved better results compared to a number of state of the art PCA variants.
引用
收藏
页码：123 / 127
页数：5
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