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Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)
A New Face Recognition Method Based on 2DWPCA
Haier International Training Center, Qingdao, China
July 30-August 01
ISBN: 0-7695-2909-7
ASCII Text
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Ke Han, Quan Feng, Xiu-chang Zhu, Hui-yuan Wang, "A New Face Recognition Method Based on 2DWPCA," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, vol. 1, pp. 196-199, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SNPD.2007.454,
author = {Ke Han and Quan Feng and Xiu-chang Zhu and Hui-yuan Wang},
title = {A New Face Recognition Method Based on 2DWPCA},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {1},
year = {2007},
isbn = {0-7695-2909-7},
pages = {196-199},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.454},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - A New Face Recognition Method Based on 2DWPCA
SN - 0-7695-2909-7
SP196
EP199
A1 - Ke Han,
A1 - Quan Feng,
A1 - Xiu-chang Zhu,
A1 - Hui-yuan Wang,
PY - 2007
KW - null
VL - 1
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
Ke Han, Nanjing University of Posts and Telecommunications, China
Quan Feng, Nanjing University of Posts and Telecommunications, China
Xiu-chang Zhu, Nanjing University of Posts and Telecommunications, China
Hui-yuan Wang, Shandong University, China
A new method based on Two-Dimensional Within-class Principal Component Analysis (2DWPCA) is proposed for face recognition in this paper. First, the within-class image scatter matrix of each class is calculated by using the training face samples in each class, respectively. Then, according to the within-class image scatter matrix of each class, the optimal eigenvectors of each class are computed, and are selected as the optimal projection axes of each class. Finally, a minimal distance classifier is employed to classify the given test samples. The proposed method is evaluated on the NUST603 face database. Experimental results demonstrate that the method proposed in this paper is effective and feasible.
Citation:
Ke Han, Quan Feng, Xiu-chang Zhu, Hui-yuan Wang, "A New Face Recognition Method Based on 2DWPCA," snpd, vol. 1, pp.196-199, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007
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