Feature extraction of face images using kernel approach
文献类型：会议论文
| 作者 | Wu XJ(吴晓军); Yang JY(杨静宇); Wang ST(王士同); Liu, Tongming |
| 出版日期 | 2002 |
| 会议名称 | 2nd International Conference on Image and Graphics |
| 会议日期 | August 16-18, 2002 |
| 会议地点 | Hefei, China |
| 关键词 | pattern recognition feature extraction disciminant analysis kernel approach face recognition |
| 页码 | 723-730 |
| 通讯作者 | 吴晓军 |
| 中文摘要 | Fisher discriminant methods (FDM) have been demonstrated their success in face recognition, detection, and tracking. Fisher discriminant method is based on the optimum of Fisher discriminant criterion. Recently Higher Order Statistics (HOS) has been applied to many pattern recognition problems. In this paper we investigate a generalization of FDM, Kernel Fisher discriminant methods (KFDM), for the feature extraction of face images, which is nonlinear analysis method. In conventional FDM, all the matrices including within-class scatter matrix, between-class scatter matrix and population scatter matrix are actually a second order correlation of patterns respectively, KFDM provides a replacement which takes into account of higher order correlation. Furthermore, KFDM computes the higher order statistics without the combinatorial explosion of time and memory complexity. We compare the recognition results using KFDM with conventional FDM on ORL face image database. Experimental results show that the proposed KFDM outperforms conventional FDM in face recognition. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | SECOND INTERNATION CONFERENCE ON IMAGE AND GRAPHICS, PTS 1 AND 2
 |
| 会议录出版者 | SPIE-INT SOC OPTICAL ENGINEERING |
| 会议录出版地 | BELLINGHAM |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 0-8194-4656-4 |
| WOS记录号 | WOS:000179559800105 |
| 源URL | [http://ir.sia.cn/handle/173321/19941]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室_先进制造技术研究室 |
| 推荐引用方式 GB/T 7714 | Wu XJ,Yang JY,Wang ST,et al. Feature extraction of face images using kernel approach[C]. 见:2nd International Conference on Image and Graphics. Hefei, China. August 16-18, 2002. |
入库方式： OAI收割
来源：沈阳自动化研究所
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