Sorted locally confined non-negative matrix factorization in face verification

Citation

Teoh, , ABJ and Ngo, , DCL and Neo, , HF (2005) Sorted locally confined non-negative matrix factorization in face verification. 2005 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS: VOL 1: COMMUNICATION THEORY AND SYSTEMS - VOL 2: SIGNAL PROCESSING, COMPUTATIONAL INTELLIGENCE, CIRCUITS AND SYSTEMS. pp. 820-824.

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Abstract

In this paper, we propose a face recognition technique based on modification of Non-Negative Matrix Factorization (NMF) technique, which known as Sorted Locally Confined NMF (SLC-NMF). SLC-NMF used NMF to find non negative basis images, subset of them were selected according to a discriminant factor and then processed through a series of image processing operation; to yield a set of ideal locally confined salient feature basis images. SLC-NMF illustrates perfectly local salient feature region which effectively realize "recognition by parts" paradigm for face recognition. The best performance is attained by SLC-NMF compare to the PCA, NMF and local NMF, in FERET Face Database.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 23 Aug 2011 07:36
Last Modified: 23 Aug 2011 07:36
URII: http://shdl.mmu.edu.my/id/eprint/2335

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