1 August 2003 Face recognition based on singular-value feature vectors
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Optical Engineering, 42(8), (2003). doi:10.1117/1.1588299
Abstract
Automatic human face recognition is a difficult but significant problem. A method for face recognition based on singular-value feature vectors is discussed. Three algorithms of face recognition based on singular-value feature vectors are proposed. These algorithms are face recognition using principal component analysis based on singular-value feature vectors, face recognition by Fisher linear discriminant analysis based on singular-value feature vectors, and face recognition using the discriminant Karhunen Loeve (DKL) transform based on singular-value feature vectors. Experimental results show that face recognition based on singular-value feature vectors is effective.
Quan Pan, Min-Gui Zhang, De-Long Zhou, Yong-Mei Cheng, Hong-Cai Zhang, "Face recognition based on singular-value feature vectors," Optical Engineering 42(8), (1 August 2003). http://dx.doi.org/10.1117/1.1588299
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KEYWORDS
Facial recognition systems

Principal component analysis

Ferroelectric LCDs

Feature extraction

Detection and tracking algorithms

Databases

Optical engineering

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