Supervised Fractional Eigenfaces

T. B. A. De Carvalho, A. M. Costa,M. A. A. Sibaldo,I. R. Tsang,G. D. C. Cavalcanti

2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)（2015）

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摘要

Supervised Fractional Eigenfaces (SFE) is an extension of Principal Component Analysis (PCA), which uses the fractional covariance matrix, class label information, and nonlinear data transformation to extract discriminant features. The proposed method combines techniques of two state-of-the-art feature extractors: Fractional Eigenfaces and Dual Supervised PCA. Supervised Fractional Eigenfaces was evaluated in three known face datasets and it achieved significant smaller recognition error.

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关键词

Face recognition,Principal component analysis,Fractional covariance matrix,Dimensionality reduction

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