Margin preserving projection for image set based face recognition

Authors:
Ke Fan;Wanquan Liu;Senjian An;Xiaoming Chen
Affiliations:
Department of Computing, Curtin University, WA, Australia;Department of Computing, Curtin University, WA, Australia;Department of Computing, Curtin University, WA, Australia;Department of Computing, Curtin University, WA, Australia
Venue:
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Year:
2011

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Abstract

Face images are usually taken from different camera views with different expressions and illumination. Face recognition based on Image set is expected to achieve better performance than traditional single frame based methods, because this new framework can incorporate information about variations of individual's appearance and make a decision collectively. In this paper we propose a new dimensionality reduction method for image set based face recognition. In the proposed method, we transform each image set into a convex hull and use support vector machine to compute margins between each pair sets. Then we use PCA to do dimension reduction with an aim to preserve those margins. Finally we do classification using a distance based on convex hull in low dimension feature space. Experiments with benchmark face video databases validate the proposed approach.