A View Independent Video-Based Face Recognition Method Using Posterior Probability in Kernel Fisher Discriminant Space(Face, Gesture, and Action Recognition,<Special Section>Machine Vision Applications)

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概要

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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.

• 社団法人電子情報通信学会の論文
• 2006-07-01

著者

• Hotta Kazuhiro

  University Of Electro-communications

関連論文

• A View Independent Video-Based Face Recognition Method Using Posterior Probability in Kernel Fisher Discriminant Space(Face, Gesture, and Action Recognition,Machine Vision Applications)
• A Robust Object Tracking Method under Pose Variation and Partial Occlusion(Tracking,Machine Vision Applications)

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