Face recognition based on singular-value feature vectors

Quan Pan; Min Gui Zhang; De Long Zhou; Yong Mei Cheng; Hong Cai Zhang

doi:10.1117/1.1588299

Face recognition based on singular-value feature vectors

Quan Pan
, Min Gui Zhang
, De Long Zhou
, Yong Mei Cheng
, Hong Cai Zhang

School of Automation

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

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.

Original language	English
Pages (from-to)	2368-2374
Number of pages	7
Journal	Optical Engineering
Volume	42
Issue number	8
DOIs	https://doi.org/10.1117/1.1588299
State	Published - Aug 2003

Keywords

Algebraic feature extraction
Dimensionality reduction
Discriminant vector
Face recognition
Facial image recognition
Singular-value feature vectors

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10.1117/1.1588299

Cite this

@article{2fcb49681f4b458bb529430b989a28ba,

title = "Face recognition based on singular-value feature vectors",

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.",

keywords = "Algebraic feature extraction, Dimensionality reduction, Discriminant vector, Face recognition, Facial image recognition, Singular-value feature vectors",

author = "Quan Pan and Zhang, \{Min Gui\} and Zhou, \{De Long\} and Cheng, \{Yong Mei\} and Zhang, \{Hong Cai\}",

year = "2003",

month = aug,

doi = "10.1117/1.1588299",

language = "英语",

volume = "42",

pages = "2368--2374",

journal = "Optical Engineering",

issn = "0091-3286",

publisher = "SPIE",

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TY - JOUR

T1 - Face recognition based on singular-value feature vectors

AU - Pan, Quan

AU - Zhang, Min Gui

AU - Zhou, De Long

AU - Cheng, Yong Mei

AU - Zhang, Hong Cai

PY - 2003/8

Y1 - 2003/8

N2 - 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.

AB - 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.

KW - Algebraic feature extraction

KW - Dimensionality reduction

KW - Discriminant vector

KW - Face recognition

KW - Facial image recognition

KW - Singular-value feature vectors

UR - https://www.scopus.com/pages/publications/0141629439

U2 - 10.1117/1.1588299

DO - 10.1117/1.1588299

M3 - 文章

AN - SCOPUS:0141629439

SN - 0091-3286

VL - 42

SP - 2368

EP - 2374

JO - Optical Engineering

JF - Optical Engineering

IS - 8

ER -

Face recognition based on singular-value feature vectors

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Keywords

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