A novel Fisher criterion based S-t-subspace linear discriminant method for face recognition
文献类型：期刊论文
| 作者 | Chen, WS; Yuen, PC; Huang, J; Lai, JH |
| 刊名 | COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS
 |
| 出版日期 | 2005 |
| 卷号 | 3801页码:933-940 |
| ISSN号 | 0302-9743 |
| 英文摘要 | In this paper, a novel Fisher criterion is introduced and shown to be equivalent to the traditional Fisher criterion. Based on this new Fisher criterion and simultaneous diagonalization technique, a S-t-subspace Fisher discriminant (S-t-SFD) method is developed to deal with the small sample size (S3) problem in face recognition. The proposed method overcomes some drawbacks of existing LDA based algorithms. Also, our method has good computational complexity. Two public available databases, namely ORL and FERET databases, are exploited to evaluate the proposed algorithm. Comparing with existing LDA-based methods in solving the S3 problem, the proposed S-t-SFD method gives the best performance. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000234873700139 |
| 出版者 | SPRINGER-VERLAG BERLIN |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/1760]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Chen, WS |
| 作者单位 | 1.Shenzhen Univ, Dept Math, Shenzhen 518060, Peoples R China 2.CAS, Key Lab Math Mechanizat, Beijing 100080, Peoples R China 3.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, WS,Yuen, PC,Huang, J,et al. A novel Fisher criterion based S-t-subspace linear discriminant method for face recognition[J]. COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS,2005,3801:933-940. |
| APA | Chen, WS,Yuen, PC,Huang, J,&Lai, JH.(2005).A novel Fisher criterion based S-t-subspace linear discriminant method for face recognition.COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS,3801,933-940. |
| MLA | Chen, WS,et al."A novel Fisher criterion based S-t-subspace linear discriminant method for face recognition".COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS 3801(2005):933-940. |
入库方式： OAI收割
来源：数学与系统科学研究院
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