Sequential face recognition based on LVQ networks

Author

Jun, Yan ; Wang Dian-hong

Author_Institution

Sch. of Mech. & Electron., China Univ. of Geosci., Hubei, China

fYear

2005

fDate

28-30 May 2005

Firstpage

284

Lastpage

287

Abstract

This paper proposes a face recognition method based on PCA and LVQ neural networks. PCA is applied to get the eigen vector of the images, then these eigen values are used as the input of the learning vector quantization networks, and the output of LVQ networks are the result of classification. Experiments on Cambridge ORL database are provided, The promising results clearly demonstrate the effectiveness of this method.

Keywords

eigenvalues and eigenfunctions; face recognition; image sequences; neural nets; principal component analysis; vector quantisation; Cambridge ORL database; PCA; eigen values; eigen vector; learning vector quantization neural networks; sequential face recognition; Covariance matrix; Eigenvalues and eigenfunctions; Electronic mail; Face recognition; Geoscience; Image processing; Image reconstruction; Neural networks; Principal component analysis; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

VLSI Design and Video Technology, 2005. Proceedings of 2005 IEEE International Workshop on

Print_ISBN

0-7803-9005-9

Type

conf

DOI

10.1109/IWVDVT.2005.1504606

Filename

1504606

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1937782