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A Study on Facial Wrinkle Detection using Active Appearance Models

AAM을 이용한 얼굴 주름 검출에 관한 연구

  • 이상범 (단국대학교 컴퓨터 과학과) ;
  • 김태묵 (단국대학교 컴퓨터 과학과)
  • Received : 2014.04.05
  • Accepted : 2014.07.20
  • Published : 2014.07.28

Abstract

In this paper, a weighted value wrinkle detection method is suggested based on the analysis on the entire facial features such as face contour, face size, eyes and ears. Firstly, the main facial elements are detected with AAM method entirely from the input screen images. Such elements are mainly composed of shape-based and appearance methods. These are used for learning the facial model and for matching the face from new screen images based on the learned models. Secondly, the face and background are separated in the screen image. Four points with the biggest possibilities for wrinkling are selected from the face and high wrinkle weighted values are assigned to them. Finally, the wrinkles are detected by applying Canny edge algorithm for the interested points of weighted value. The suggested algorithm adopts various screen images for experiment. The experiments display the excellent results of face and wrinkle detection in the most of the screen images.

Keywords

Active Appearance Model;Canny edge;Gaussian Filter;Grab-cut;hough line detection;Wrinkle Detection;Weight wrinkle

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