Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

L1-norm-based (2D)2PCA

Authors
Fujin Zhong
Corresponding Author
Fujin Zhong
Available Online March 2013.
DOI
10.2991/iccsee.2013.324How to use a DOI?
Keywords
bidirectional two-dimension principal component analysis, l2-norm, outliers, L1-norm, Optimization
Abstract

Traditional bidirectional two-dimension (2D) principal component analysis ((2D)2PCA-L2) is sensitive to outliers because its objective function is the least squares criterion based on L2-norm. This paper proposes a simple but effective L1-norm-based bidirectional 2D principal component analysis ((2D)2PCA-L1), which jointly takes advantage of the merits of bidirectional 2D subspace learning and L1-norm-based distance criterion. Experimental results on two popular face databases show that the proposed method is more robust to outliers than several methods based on principal component analysis in the fields of data compression and object recognition.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
10.2991/iccsee.2013.324
ISSN
1951-6851
DOI
10.2991/iccsee.2013.324How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fujin Zhong
PY  - 2013/03
DA  - 2013/03
TI  - L1-norm-based (2D)2PCA
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1293
EP  - 1296
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.324
DO  - 10.2991/iccsee.2013.324
ID  - Zhong2013/03
ER  -