Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding

Eimad Eldin A A Abusham, David Ngo, Andrew Teoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Among the many methods proposed in the literature for face recognition, those relying on face manifold have been explored with great interest in the last few years.In those methods theface images are initially subjected to dimensional reduction and then applied to a classifier.In this paper we evaluate and compare two novel approaches for face recognition to address thechallenging task of recognition using a fusion of nonlinear dimensional reduction;Locally Linear Embedding (LLE) integrated with Principal Component Analysis (LLEPCA) and LLE with RBF network (LLERBF).Extensive experiments using the CMU AMP Face EXpression Database and JAFFE databases indicate that PCA is faster than RBF in regard to computation time when we measured the CPU time.The difference was almost 1.2 second when we run both algorithms on the same data.

Original languageEnglish
Title of host publicationInternational Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005
Pages78-82
Number of pages5
Publication statusPublished - 2005 Dec 1
Event14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005 - Toronto, ON, Canada
Duration: 2005 Jul 202005 Jul 22

Other

Other14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005
CountryCanada
CityToronto, ON
Period05/7/2005/7/22

Fingerprint

Face recognition
Principal component analysis
Radial basis function networks
Program processors
Classifiers
Fusion reactions
Experiments

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Software

Cite this

Abusham, E. E. A. A., Ngo, D., & Teoh, A. (2005). Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding. In International Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005 (pp. 78-82)
Abusham, Eimad Eldin A A ; Ngo, David ; Teoh, Andrew. / Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding. International Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005. 2005. pp. 78-82
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Abusham, EEAA, Ngo, D & Teoh, A 2005, Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding. in International Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005. pp. 78-82, 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005, Toronto, ON, Canada, 05/7/20.

Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding. / Abusham, Eimad Eldin A A; Ngo, David; Teoh, Andrew.

International Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005. 2005. p. 78-82.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abusham EEAA, Ngo D, Teoh A. Comparing the performance of principal component analysis and rbf network for face recognition using locally linear embedding. In International Society for Computers and their Applications - 14th International Conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2005. 2005. p. 78-82