Advanced Research in Applied Artificial Intelligence

Volume 7345 of the series Lecture Notes in Computer Science pp 1-9

Automatic Detailed Localization of Facial Features

  • Qing HeAffiliated withDepartment of Computer Science, University of Missouri
  • , Ye DuanAffiliated withDepartment of Computer Science, University of Missouri
  • , Danyang ZhangAffiliated withDepartment of Mathematics and Computer Science, York College, The City University of New York

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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.


facial feature localization eyelid nose boundary lip contour generalized Hough transform