Direct Orthogonal Marginal Fisher Analysis

Yue Lin; Jing Zhao Li; Xing Zhu Liang

doi:10.4028/www.scientific.net/AMR.468-471.1203

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Direct Orthogonal Marginal Fisher Analysis

Direct Orthogonal Marginal Fisher Analysis

Abstract:

The recently proposed Marginal Fisher Analysis (MFA) achieved high performance for face recognition. However, MFA suffers from the small sample size problem and the optimal basis vectors obtained by the MFA are nonorthogonal. In this paper, we present a new method called Direct Orthogonal Marginal Fisher Analysis (DOMFA), which is able to extract all the orthogonal discriminant vectors simultaneously in the high-dimensional feature space without pre-processing using PCA and does not suffer the small sample size problem. Experimental results on ORL database indicate that the proposed DOMFA method achieves better recognition rate than the MFA method and some other orthogonal feature extraction algorithms.

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Periodical:

Advanced Materials Research (Volumes 468-471)

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1203-1206

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.1203

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Online since:

February 2012

Authors:

Yue Lin, Jing Zhao Li, Xing Zhu Liang

Keywords:

Direct Orthogonal Marginal Fisher Analysis, Face Recognition, Orthogonal Discriminant Vectors, Small Sample Size Problem

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