@inproceedings{489cf82bd68b443eb431bbfec08a1976,
title = "Multi-eigenspace learning for video-based face recognition",
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.",
keywords = "Face recognition, Incremental principal component analysis, Online learning",
author = "Liang Liu and Yunhong Wang and Tieniu Tan",
year = "2007",
doi = "10.1007/978-3-540-74549-5\_20",
language = "英语",
isbn = "3540745483",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "181--190",
booktitle = "Advances in Biometrics - International Conference, ICB 2007, Proceedings",
address = "德国",
note = "2007 International Conference on Advances in Biometrics, ICB 2007 ; Conference date: 27-08-2007 Through 29-08-2007",
}