Cascade MR-ASM for Locating Facial Feature Points

  • Sicong Zhang
  • Lifang Wu
  • Ying Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


Accurate and robust location of feature point is a difficult and challenging issue in face recognition. In this paper we propose a new approach of using a cascade of Multi-Resolution Active Shape Models (C-MR-ASM) to locate facial feature points. In our approach, more than one MR-ASMs are obtained from different subsets of training set automatically, and these MR-ASMs are integrated in a cascade to locate facial feature points. Experimental results show that our algorithm is more accurate than traditional MR-ASM. The contribution of this paper includes: 1, unlike traditional MR-ASM, the training set is divided into several subsets automatically based on the principle a trained model should describe all the samples in training set accurately. 2, we propose the new cascade framework, which integrates all the subset MR-ASM.


Training Sample Feature Point Face Recognition Gray Level Face Image 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Sicong Zhang
    • 1
  • Lifang Wu
    • 1
  • Ying Wang
    • 1
  1. 1.School of Electronic Information and control Engineering, Beijing University of Technology, Beijing, 100022China

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