Abstract

We propose a complete framework for automatic detailed facial feature localization. Feature points and contours of the eyes, the nose, the mouth and the chin are of interest. Face detection is performed followed by the region detection that locates a rough bounding box of each facial component, and detailed features are then extracted within each bounding box. Since the feature points lie on the shape contours, we start from shape contour extraction, and then detect the feature points from the extracted contours. Experimental results show the robustness and accuracy of our methods. The main application of our work is automatic diagnosis based on facial features.

Keywords

facial feature localization eyelid nose boundary lip contour generalized Hough transform 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Qing He
    • 1
  • Ye Duan
    • 1
  • Danyang Zhang
    • 2
  1. 1.Department of Computer ScienceUniversity of MissouriColumbiaUSA
  2. 2.Department of Mathematics and Computer Science, York CollegeThe City University of New YorkJamaicaUSA

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