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http://dx.doi.org/10.14400/JDC.2014.12.7.239

A Study on Facial Wrinkle Detection using Active Appearance Models  

Lee, Sang-Bum (Dankook Uni. Dept. of Computer Science)
Kim, Tae-Mook (Dankook Uni. Dept. of Computer Science)
Publication Information
Journal of Digital Convergence / v.12, no.7, 2014 , pp. 239-245 More about this Journal
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;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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