L1-norm-based 2DPCA

Li, Xuelong and Pang, Y. and Yuan, Y. (2010) L1-norm-based 2DPCA. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 (4), pp. 1170-1175. ISSN 1083-4419.

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Official URL: http://dx.doi.org/10.1109/TSMCB.2009.2035629

Abstract

In this paper, we first present a simple but effective L1-norm-based two-dimensional principal component analysis (2DPCA). Traditional L2-norm-based least squares criterion is sensitive to outliers, while the newly proposed L1-norm 2DPCA is robust. Experimental results demonstrate its advantages.

Metadata

Item Type:	Article
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	20 Jun 2013 13:05
Last Modified:	09 Aug 2023 12:33
URI:	https://eprints.bbk.ac.uk/id/eprint/7536

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