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Titolo:
Face recognition using holistic Fourier invariant features
Autore:
Lai, JH; Yuen, PC; Feng, GC;
Indirizzi:
Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China Hong Kong Baptist Univ Hong Kong Hong Kong Peoples R China oples R China Zhongshan Univ, Dept Math, Guangzhou, Peoples R China Zhongshan Univ Guangzhou Peoples R China th, Guangzhou, Peoples R China
Titolo Testata:
PATTERN RECOGNITION
fascicolo: 1, volume: 34, anno: 2001,
pagine: 95 - 109
SICI:
0031-3203(200101)34:1<95:FRUHFI>2.0.ZU;2-R
Fonte:
ISI
Lingua:
ENG
Soggetto:
FEATURE-EXTRACTION; DEFORMABLE TEMPLATES; FRONTAL-VIEW; IMAGES; EYE; REPRESENTATION; DECOMPOSITION; EIGENFACES; PROJECTION; SHAPE;
Keywords:
face recognition; Fourier transform; wavelet transform; spectroface;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
43
Recensione:
Indirizzi per estratti:
Indirizzo: Yuen, PC Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China Hong Kong Baptist Univ Hong Kong Hong Kong Peoples R China hina
Citazione:
J.H. Lai et al., "Face recognition using holistic Fourier invariant features", PATT RECOG, 34(1), 2001, pp. 95-109

Abstract

This paper presents a new method for holistic face representation, called spectroface. Spectroface representation combines the wavelet transform and the Fourier transform. We have shown that by decomposing a face image usingwavelet transform, the low-frequency face image is less sensitive to the facial expression variations. This paper also proves that the spectroface representation is invariant to translation, scale and on-the-plane rotation. To handle the rotation in depth, multiple view images are used to determinethe reference image representation. Based on the spectroface representation, a face recognition system is designed and developed. Yale and Olivetti face databases are selected to evaluate the proposed system. These two databases contain 55 persons with 565 face images at different orientations, scale, facial expressions, small occlusions and different illuminations. The recognition accuracy is over 94%. If we consider the top three matches, the accuracy is over 98%. The recognition system is developed on Pentium 200 MHz computer and the recognition time is less than 3 seconds for database with 55 persons (C) 2000 Pattern Recognition Scociety. Published by Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 27/01/20 alle ore 01:20:30