Combining cascade PCA and face shape models for robust registration

Guangpeng Zhang; Yunhong Wang

doi:10.1117/12.777365

17 March 2008 Combining cascade PCA and face shape models for robust registration

Guangpeng Zhang, Yunhong Wang

Proceedings Volume 6944, Biometric Technology for Human Identification V; 69440Q (2008) https://doi.org/10.1117/12.777365
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

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Guangpeng Zhang and Yunhong Wang "Combining cascade PCA and face shape models for robust registration", Proc. SPIE 6944, Biometric Technology for Human Identification V, 69440Q (17 March 2008); https://doi.org/10.1117/12.777365

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KEYWORDS

Principal component analysis

3D modeling

3D image processing

Data modeling

Image registration

Facial recognition systems

3D scanning

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