Face Recognition Based on PCA/KPCA Plus CCA
| العنوان: | Face Recognition Based on PCA/KPCA Plus CCA |
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| المؤلفون: | Yun-Hui He, Li Zhao, Cairong Zou |
| المصدر: | Lecture Notes in Computer Science ISBN: 9783540283256 ICNC (2) |
| بيانات النشر: | Springer Berlin Heidelberg, 2005. |
| سنة النشر: | 2005 |
| مصطلحات موضوعية: | business.industry, Feature extraction, Pattern recognition, Linear discriminant analysis, Facial recognition system, symbols.namesake, Discriminant, Scatter matrix, Principal component analysis, symbols, Artificial intelligence, Fisher information, business, Canonical correlation, Mathematics |
| الوصف: | Based on the equivalence between canonical correlation analysis (CCA) and Fisher linear discriminant analysis (FLDA), two methods for feature extraction of face images are proposed in this paper. In the first approach, the high-dimensional face images are first mapped into the range space of total scatter matrix using principle component analysis (PCA). Then CCA is performed to extract the linear optimal discriminant features without losing Fisher discriminatory information. In the second approach, nonlinear features are extracted using KPCA+CCA which is equivalent to KFDA in nature. The experimental results upon ORL face database indicate that the proposed PCA/KPCA+CCA significantly outperform the traditional Fisherface method. |
| ردمك: | 978-3-540-28325-6 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::e0924d6c22e9e7e39b34118919e0bc62 https://doi.org/10.1007/11539117_11 |
| رقم الأكسشن: | edsair.doi...........e0924d6c22e9e7e39b34118919e0bc62 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783540283256 |
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