Abstract
It is well-known that the distribution of face images with different pose, illumination and face expression is complex and nonlinear. The traditional linear methods, such as linear discriminant analysis (LDA), will not give a satisfactory performance. In addition, LDA always suffers from small sample size (S3) problem, which always occurs when the sample size is smaller than the dimensionality of feature vector. To overcome these limitations, Shannon wavelet kernel combining with subspace LDA (SWKSLDA) algorithm is developed. Two databases, namely FERET and CMU PIE databases, are selected for evaluation. Comparing with the existing LDA-based methods, the proposed method gives superior results.
Original language | English |
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Title of host publication | 2006 International Conference on Computational Intelligence and Security, CIS 2006 |
Publisher | IEEE Computer Society |
Pages | 708-713 |
Number of pages | 6 |
ISBN (Electronic) | 1424406056 |
ISBN (Print) | 1424406048, 9781424406050 |
DOIs | |
Publication status | Published - 3 Nov 2006 |
Event | 2006 International Conference on Computational Intelligence and Security, CIS 2006 - Guangzhou, China Duration: 3 Nov 2006 → 6 Nov 2006 https://ieeexplore.ieee.org/xpl/conhome/4072023/proceeding https://link.springer.com/book/10.1007/978-3-540-74377-4 |
Publication series
Name | International Conference on Computational Intelligence and Security, CIS |
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Conference
Conference | 2006 International Conference on Computational Intelligence and Security, CIS 2006 |
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Country/Territory | China |
City | Guangzhou |
Period | 3/11/06 → 6/11/06 |
Internet address |
Scopus Subject Areas
- General Computer Science
- Control and Systems Engineering