DocumentCode :
2043398
Title :
Extension of the MPEG-7 Fourier Feature Descriptor for face recognition using PCA
Author :
Zaeri, Naser ; Mokhtarian, Farzin ; Cherri, Abdallah
Author_Institution :
Center for Vision, Speech & Signal Process., Univ. of Surrey, Guildford, UK
fYear :
2006
fDate :
20-22 March 2006
Firstpage :
1
Lastpage :
6
Abstract :
The Principal Component Analysis or the eigenface technique provides a practical solution to the problem of face recognition. Recently, many face descriptors for MPEG-7 have been proposed for face retrieval in video streams. In this paper, a new method for face recognition is presented based on extracting the most discriminant features of the MPEG-7 Fourier Feature Descriptors of the face space, defined by MPEG-7 face recognition technique, through the implementation of the eigenface technique. It will be demonstrated that the proposed method improves the recognition rate and copes better with pose variations under different facial expressions and varying face conditions, as well as illumination variations. In addition, the proposed method achieves substantial savings in the computation time needed by the recognition system.
Keywords :
Fourier analysis; eigenvalues and eigenfunctions; face recognition; image retrieval; principal component analysis; video streaming; MPEG-7 Fourier feature descriptor; MPEG-7 face recognition technique; PCA; eigenface technique; face retrieval; illumination variations; principal component analysis; video stream; Covariance matrix; Databases; Face; Face recognition; Feature extraction; Principal component analysis; Transform coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
GCC Conference (GCC), 2006 IEEE
Conference_Location :
Manama
Print_ISBN :
978-0-7803-9590-9
Electronic_ISBN :
978-0-7803-9591-6
Type :
conf
DOI :
10.1109/IEEEGCC.2006.5686244
Filename :
5686244
Link To Document :
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