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Constraint Shape Model Using Edge Constraint and Gabor Wavelet Based Search

  • Baochang Zhang
  • Wen Gao
  • Shiguang Shan
  • Wei Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2688)

Abstract

Constraint Shape Model is proposed to extract facial feature using two different search methods for contour points and control points individually. In the proposed algorithm, salient facial features, such as the eyes and the mouth, are first localized and utilized to initialize the shape model and provide region constraints on iterative shape searching. For the landmarks on the face contour, the edge intensity is exploited to construct better local texture matching models. Moreover, for control points, the proposed Gabor wavelet based method is used to search it by multi-frequency strategy. To test the proposed approaches, on a database containing 500 labeled face images, experiments are conducted, which shows that the proposed method performs significantly better in terms of a deliberate performance evaluation method. The proposed method can be easily used to other texture objects, which is robust to variations in illumination and facial expression.

Keywords

Shape Model Gabor Wavelet Facial Feature Extraction 

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References

  1. [1]
    M. Kass, A. Witkin and D. Terzopoulos, “Active contour models” 1st international conference on Computer Vision, London, June 1987, pp.259–268.Google Scholar
  2. [2]
    L. Wiskott, J.M. Fellous, N. Kruger, C.v.d. Malsburg, Face Recogniton by Elastic Bunch Graph Matching, IEEE Trans. On PAMI, Vol.19, No. 7, 1997.Google Scholar
  3. [3]
    T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham, “Active shape models-their training and application,” Copmuter Vision and Image understanding, 61(1): pp38–59, 1995.CrossRefGoogle Scholar
  4. [4]
    T. Cootes, G.J. Edwards, and C.J. Taylor, “Active appearance models,” in Proceeding of 5th European Conference on Computer Vision, 1998, vol. 2, pp.Google Scholar
  5. [5]
    M. Rogers & J. Graham. “Robust active shape model search.” In Proceedings of the European Conference on Computer Vision. May 2002.Google Scholar
  6. [6]
    B. Cao, S.G. Shan, W. Gao, Localizing the iris center by region growing search, Proceeding of the ICME2002.Google Scholar
  7. [7]
    Wei Wang, Shiguan Shan, etc. An Improved Active Shape Model For Face Alignment, ICMI02.Google Scholar
  8. [8]
    J.G. Daugman, “Two-dimensional spectral analysis of cortical receptive field profiles,” Vision Research, vol. 20, pp. 847–856, 1980.CrossRefGoogle Scholar
  9. [9]
    Chengjun Liu and Harry Wechsler,“Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition” IEEE Trans. Image Processing vol.11 no.4 2002.Google Scholar
  10. [10]
    L. Wiskott, J.M. Fellous, N. Kruger, and C. von der Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775–779, 1997.CrossRefGoogle Scholar
  11. [11]
    F. Smeraldi and J. Bigun. Retinal vision applied to facial features detection and face authentication. Pattern Recognition Letters, 23:463–475, 2002.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Baochang Zhang
    • 1
  • Wen Gao
    • 1
    • 2
  • Shiguang Shan
    • 2
  • Wei Wang
    • 3
  1. 1.Computer CollegeHarbin Institute of TechnologyHarbinChina
  2. 2.ICT-YCNC FRJDLInstitute of Computing Technology CASBeijingChina
  3. 3.College of Computer ScienceBeijing Polytechnic UniversityBeijingChina

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