| Autor: |
Singh, Sameer, Singh, Maneesha, Apte, Chid, Perner, Petra, Hotta, Kazuhiro |
| Zdroj: |
Pattern Recognition & Image Analysis (9783540288336); 2005, p103-111, 9p |
| Abstrakt: |
This paper presents a view independent video-based face recognition method using posterior probability in Kernel Fisher Discriminant (KFD) space. In practical environment, the view of faces changes dynamically. The robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induces large non-linear variation, kernel-based methods are appropriate. We use KFD analysis to cope with non-linear variation. To classify image sequence, the posterior probability in KFD space is used. KFD analysis assumes that the distribution of each class in high dimensional space is Gaussian. This makes the computation of posterior probability in KFD space easy. The effectiveness of the proposed method is shown by the comparison with the other feature spaces and classification methods. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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