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A View Independent Video-Based Face Recognition Method Using Posterior Probability in Kernel Fisher Discriminant Space
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2006/07/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Machine Vision Applications)
Category: Face, Gesture, and Action Recognition
view independence, video-based face recognition, posterior probability, kernel Fisher discriminant analysis,
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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. Robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induce 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 combination of KFD space and posterior probability of image sequence is the main contribution of the proposed method. The performance is evaluated by using two face databases. Effectiveness of the proposed method is shown by the comparison with the other feature spaces and classification methods.