Facecut - a robust approach for facial feature segmentation

Segmentation of facial features is a key pre-processing step in enabling facial recognition, building of 3D facial models, expression analysis, and pose estimation. Recently, graph cuts based algorithms have been adapted to carry out this task but many of these methods require manual initialization...

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Bibliographic Details
Published in2012 19th IEEE International Conference on Image Processing pp. 1841 - 1844
Main Authors Khoa Luu, Le, T. H. N., Seshadri, K., Savvides, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Active Shape Models (ASMs)
Face
Face segmentation
FaceCut
Facial features
facial landmarks
graph cuts
Image color analysis
Image segmentation
Shape
Skin
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Summary:Segmentation of facial features is a key pre-processing step in enabling facial recognition, building of 3D facial models, expression analysis, and pose estimation. Recently, graph cuts based algorithms have been adapted to carry out this task but many of these methods require manual initialization of points in the foreground and background. In this paper, we propose a novel and fully automatic approach, named Face-Cut, to perform accurate facial feature segmentation. FaceCut combines the positive features of the Modified Active Shape Model (MASM) and GrowCut algorithms to ensure highly accurate and completely automatic segmentation of facial features. We demonstrate the effectiveness of FaceCut on images from two challenging databases.
ISBN:1467325341
9781467325349
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2012.6467241