@inproceedings{4f6fa10ccffe44f6869d6c1835177d78,
title = "Improved parameters estimating scheme for E-HMM with application to face recognition",
abstract = "This paper presents a new scheme to initialize and re-estimate Embedded Hidden Markov Models(E-HMM) parameters for face recognition. Firstly, the current samples were assumed to be a subset of the whole training samples, after the training process, the E-HMM parameters and the necessary temporary parameters in the parameter re-estimating process were saved for the possible retraining use. When new training samples were added to the training samples, the saved E-HMM parameters were chosen as the initial model parameter. Then the E-HMM was retrained based on the new samples and the new temporary parameters were obtained. Finally, these temporary parameters were combined with saved temporary parameters to form the final E-HMM parameters for representing one person face. Experiments on ORL databases show the improved method is effective.",
author = "Bindang Xue and Wenfang Xue and Zhiguo Jiang",
year = "2006",
doi = "10.1007/11608288\_27",
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 = "199--205",
booktitle = "Advances in Biometrics - International Conference, ICB 2006, Proceedings",
address = "德国",
note = "2006 International Conference on Biometrics, ICB 2006 ; Conference date: 05-01-2006 Through 07-01-2006",
}