Face recognition using independent component analysis based on restricted mean field approximation

LIU Zhi-fang; YOU Zhi-sheng; Zhang Ji-ping

Based on mean field approximation a new method is proposed to solve noisy ICA model,which can fairly well solve over-complete case,and estimate the independent source by restrict the non-negative mixing matrix and the non-negative sources.The experiments have been done for several different cases,such as digital images,simulated face graphics and ORL face database.The digital images and simulated face graphics experiments show the extraction features by the RMFA-ICA are more independent than that of using tradition ICA and unrestrictive MFA-ICA,the ORL face recognition experiments show the recognition ratio by the proposed method is greater than that of using the others methods.

1. Institute of Image & Graphic, College of Computer Science, Sichuan University, Chengdu 610065, China;

2. School of Automation Engineering, University Electronic Science and Technology of China, Chengdu 610054, China

Received Date: 2004-06-14

Accepted Date: 2004-10-10

Available Online: 2005-11-25

Abstract: Based on mean field approximation a new method is proposed to solve noisy ICA model,which can fairly well solve over-complete case,and estimate the independent source by restrict the non-negative mixing matrix and the non-negative sources.The experiments have been done for several different cases,such as digital images,simulated face graphics and ORL face database.The digital images and simulated face graphics experiments show the extraction features by the RMFA-ICA are more independent than that of using tradition ICA and unrestrictive MFA-ICA,the ORL face recognition experiments show the recognition ratio by the proposed method is greater than that of using the others methods.

HTML

Reference (9)

[1]	COMON P.Independent component analysis,a new concept[J].Signal Processing,1994,36(3):287～314.
[2]	HYVARINEN A.Survey on independent component analysis[J].Neural Computing Surveys,1999,1(2):94～128.
[3]	LEWICKI M S.Learning overcomplete representations[J].NeuralComputation,2000,12(2):337～365.
[4]	PETERSON A.A mean field theory learning algorithm for neural networks[J].Complex Systems,1987,24(1):995～1019.
[5]	ATTIAS H.Independent factor analysis[J].Neural Computation,1999,11(4):803～851.
[6]	TANAKA T.A theory of mean field approximation[A].Advances in Neural Information Processing Systems[C].Massachustts:MIT Press,1999.351～357.
[7]	HYVARINEN A,KARTHIKESH R.Sparse priors on the mixing matrix in ICA[A].Proc Int Workshop on ICA and BSS (ICA2000)[C].Helsinki:Helsinki University Press,2000.477～452.
[8]	刘直芳,游志胜,王运琼.基于PCA和ICA的人脸识别[J].激光技术,2004,28(1):78～81.
[9]	刘直芳.人脸检测和识别的研究[D].成都:四川大学,2004.146～147.

Face recognition using independent component analysis based on restricted mean field approximation

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Proportional views