Multi-eigenspace learning for video-based face recognition

Authors:
Liang Liu;Yunhong Wang;Tieniu Tan
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;School of Computer Science and Engineering, Beihang University, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

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Abstract

In this paper, we propose a novel online learning method called Multi-Eigenspace Learning which can learn appearance models incrementally from a given video stream. For each subject, we try to learn a few eigenspace models using IPCA (Incremental Principal Component Analysis). In the process of Multi-Eigenspace Learning, each eigenspace generally contains more and more samples except one eigenspace which contains the least number of samples. Then, these learnt eigenspace models are used for video-based face recognition. Experimental results show that the proposed method can achieve high recognition rate.