DocumentCode :
3063013
Title :
Automatic and efficient 3D face feature segmentation with active contours
Author :
Krueger, M. ; Delmas, P. ; Gimel´farb, G.
Author_Institution :
Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
fYear :
2009
fDate :
23-25 Nov. 2009
Firstpage :
165
Lastpage :
170
Abstract :
3D face analysis is a field of growing interest in the applied Computer Vision community, its applications including face recognition, modelling and biometrics, virtual and augmented reality. While several works exist on the extraction of feature points from 3D face data, there is so far no automatic system for 3D face feature contour segmentation. This paper focuses on the later problem: we aim to fill this gap. Starting from a 3D range image, bounding boxes for the face features of interest are determined first. Then the feature boundaries are segmented accurately using globally optimal and quasi-optimal active contour (AC) methods. Both AC approaches incorporate shape priors to make features more robust under noise. Evaluation on a test database shows that the proposed system yields accurate segmentation results of lip and eye contours for 96% and 85% of the datasets, respectively.
Keywords :
edge detection; face recognition; feature extraction; image segmentation; 3D face analysis; 3D face feature contour segmentation; active contours; feature points extraction; Active contours; Application software; Augmented reality; Biometrics; Computer vision; Data mining; Face detection; Face recognition; Feature extraction; Image segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference
Conference_Location :
Wellington
ISSN :
2151-2205
Print_ISBN :
978-1-4244-4697-1
Electronic_ISBN :
2151-2205
Type :
conf
DOI :
10.1109/IVCNZ.2009.5378419
Filename :
5378419
Link To Document :
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