A Random Network Ensemble for Face Recognition

Authors:
Kwontaeg Choi;Kar-Ann Toh;Hyeran Byun
Affiliations:
Dept. of Computer Science, Yonsei University, Seoul, South Korea 120-749;School of Electrical & Electronic Engineering, Yonsei University, Seoul, South Korea 120-749;Dept. of Computer Science, Yonsei University, Seoul, South Korea 120-749
Venue:
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Year:
2009

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Abstract

In this paper, we propose a random network ensemble for face recognition problem, particularly for images with a large appearance variation and with a limited number of training set. In order to reduce the correlation within the network ensemble using a single type of feature extractor and classifier, localized random facial features have been constructed together with internally randomized networks. The ensemble classifier is finally constructed by combining these multiple networks via a sum rule. The proposed method is shown to have a better accuracy(31.5% and 15.3% improvements on AR and EYALEB databases respectively) and a better efficiency than that of the widely used PCA-SVM.