Radial basis function neural network with incremental learning for face recognition

Yee Wan Wong; Kah Phooi Seng; Li-Minn Ang

doi:10.1109/TSMCB.2010.2101591

Back

Radial basis function neural network with incremental learning for face recognition

Journal article

Peer reviewed

Radial basis function neural network with incremental learning for face recognition

Yee Wan Wong, Kah Phooi Seng and Li-Minn Ang

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol.41(4), pp.940-949

2011

DOI: https://doi.org/10.1109/TSMCB.2010.2101591

PMID: 21245011

Files and links (1)

url

https://doi.org/10.1109/TSMCB.2010.2101591View

Published Version

Abstract

face recognition

incremental learning

neural network

orthogonal least square

radial basis function (RBF)

visual variation

Conventional face recognition suffers from problems such as extending the classifier for newly added people and learning updated information about the existing people. The way to address these problems is to retrain the system which will require expensive computational complexity. In this paper, a radial basis function (RBF) neural network with a new incremental learning method based on the regularized orthogonal least square (ROLS) algorithm is proposed for face recognition. It is designed to accommodate new information without retraining the initial network. In our proposed method, the selection of the regressors for the new data is done locally, hence avoiding the expensive reselecting process. In addition, it accumulates previous experience and learns updated new knowledge of the existing groups to increase the robustness of the system. The experimental results show that the proposed method gives higher average recognition accuracy compared to the conventional ROLS-algorithm-based RBF neural network with much lower computational complexity. Furthermore, the proposed method achieves higher recognition accuracy as compared to other incremental learning algorithms such as incremental principal component analysis and incremental linear discriminant analysis in face recognition.

Details

Title: Radial basis function neural network with incremental learning for face recognition
Authors: Yee Wan Wong (Author) - University of Nottingham Malaysia Campus
Kah Phooi Seng (Author) - University of Nottingham Malaysia Campus
Li-Minn Ang (Author) - University of Nottingham Malaysia Campus
Publication details: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol.41(4), pp.940-949
Publisher: Institute of Electrical and Electronics Engineers
Date published: 2011
DOI: 10.1109/TSMCB.2010.2101591
ISSN: 1083-4419; 1941-0492; 1083-4419
PMID: 21245011
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513890302621
Output Type: Journal article

Metrics

28 Record Views

43 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Web Of Science research areas: Automation & Control Systems; Computer Science, Artificial Intelligence; Computer Science, Cybernetics