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2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. (2003)
Madison, Wisconsin
June 18, 2003 to June 20, 2003
ISSN: 1063-6919
ISBN: 0-7695-1900-8
pp: 321
Feng Jiao , University of Waterloo
Stan Li , Microsoft Research Asia
Heung-Yeung Shum , Microsoft Research Asia
Dale Schuurmans , University of Waterloo
ABSTRACT
Active Shape Model (ASM) is a powerful statistical tool for face alignment by shape. However, it can suffer from changes in illumination and facial expression changes, and local minima in optimization. In this paper, we present a method, W-ASM, in which Gabor wavelet features are used for modeling local image structure. The magnitude and phase of Gabor features contain rich information about the local structural features of face images to be aligned, and provide accurate guidance for search. To a large extent, this repairs defects in gray scale based search. An E-M algorithm is used to model the Gabor feature distribution, and a coarse-to-fine grained search is used to position local features in the image. Experimental results demonstrate the ability of W-ASM to accurately align and locate facial features.
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CITATION

D. Schuurmans, F. Jiao, H. Shum and S. Li, "Face Alignment Using Statistical Models and Wavelet Features," 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.(CVPR), Madison, Wisconsin, 2003, pp. 321.
doi:10.1109/CVPR.2003.1211370
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