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Nose Localization Based on Subclass Discriminant Analysis

  • Jiatao Song
  • Lihua Jia
  • Gang Xie
  • Wei Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 304)

Abstract

Nose localization is important for face recognition, face pose recognition, 3D face reconstruction and so on. In this paper, a novel method for nose localization is proposed. Our method includes two Subclass Discriminant Analysis (SDA) based steps. The first step locates nose from the whole face image and some randomly selected image patches are used as negative samples for the training of SDA classifier. The second step refines nose position by using some nose context patches as negative samples. The proposed method detects nose from the whole face image and no prior knowledge about the layout of face components on a face is employed. Experimental results on AR images show that the proposed method can accurately locate nose from face images, and is robust to lighting and facial expression changes.

Keywords

Nose localization subclass discriminant analysis (SDA) illumination change 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jiatao Song
    • 1
  • Lihua Jia
    • 1
    • 2
  • Gang Xie
    • 2
  • Wei Wang
    • 1
  1. 1.School of Electronic and Information EngineeringNingbo University of TechnologyNingboP.R. China
  2. 2.College of Information EngineeringTaiyuan University of TechnologyTaiyuanP.R. China

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