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Proceedings Paper

Combining cascade PCA and face shape models for robust registration
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Paper Abstract

3D facial feature point localization is very important to registration. This paper proposes a localization method that is capable of locating 3D facial feature points rapidly while achieving high localization and registration accuracy. There are two contributions of this paper. The first is the introduction of the Cascade PCA which allows the non-occluded and symmetric face models to be normalized quickly while spending more computation on occluded face models. The second is the three face shape models which are used to verify the normalization results produced by Cascade PCA, and localize dozens of feature points at the same time. Experimental results prove the efficiency and accuracy of our method both in localization and registration.

Paper Details

Date Published: 17 March 2008
PDF: 9 pages
Proc. SPIE 6944, Biometric Technology for Human Identification V, 69440Q (17 March 2008); doi: 10.1117/12.777365
Show Author Affiliations
Guangpeng Zhang, Beihang Univ. (China)
Yunhong Wang, Beihang Univ. (China)


Published in SPIE Proceedings Vol. 6944:
Biometric Technology for Human Identification V
B.V.K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editor(s)

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