Margin Preserving Projection for Image Set Based Face Recognition

  • Ke Fan
  • Wanquan Liu
  • Senjian An
  • Xiaoming Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7063)

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.

Keywords

Face recognition Dimensionality reduction Support vector machine Image set match Convex hull distance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ke Fan
    • 1
  • Wanquan Liu
    • 1
  • Senjian An
    • 1
  • Xiaoming Chen
    • 1
  1. 1.Department of ComputingCurtin UniversityAustralia

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