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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jun-Ying Gan Si-Bin He Peng Wang |
| Copyright Year | 2010 |
| Description | Author affiliation: School of Information, Wuyi University, Jiangmen, Guangdong, P.R.C. 529020 (Jun-Ying Gan; Si-Bin He; Peng Wang) |
| Abstract | In Two-Dimensional Linear Discriminant Analysis (2DLDA), it is satisfied that within-class covariance matrixes are equal; while in Two-Dimensional Heteroscedastic Discriminant Analysis (2DHDA), within-class covariance matrixes are heteroscedastic. Based on the characters of 2DLDA and 2DHDA, Weighted Two-Dimensional Heteroscedastic Discriminant Analysis (W2DHDA) is introduced and used in face recognition, in which within-class covariance matrix is defined as weighted summation of both within-class covariance matrixes of 2DLDA and 2DHDA. In this way, the defined within-class covariance matrixes in W2DHDA are more robust. Experimental results based on ORL (Olivetti Research Laboratory) and Yale mixture face database show the validity of W2DHDA in face recognition. |
| Starting Page | 649 |
| Ending Page | 652 |
| File Size | 103292 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458974 |
| e-ISBN | 9781424459001 |
| DOI | 10.1109/ICOSP.2010.5656852 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face Feature extraction Face recognition Covariance matrix Training Databases Linear discriminant analysis Weighted Two-Dimensional Heteroscedastic Discriminant Analysis Face Recognition Two-Dimensional Heteroscedastic Discriminant Analysis Two-Dimensional Linear Discriminant Analysis |
| Content Type | Text |
| Resource Type | Article |
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