10 September 2015 Expression-invariant face recognition using three-dimensional weighted walkthrough and centroid distance
Yan Liang, Yun Zhang
Author Affiliations +
Abstract
Three-dimensional (3-D) face recognition provides a potential to handle challenges caused by illumination and pose variations. However, extreme expression variations still complicate the task of recognition. An accurate and robust method for expression-invariant 3-D face recognition is proposed. A 3-D face is partitioned into a set of isogeodesic stripes and the spatial relationships of the stripes are described by 3-D weighted walkthrough and the centroid distance. Moreover, the method of the similarity measure is given. Experiments are performed on the CASIA dataset and the FRGC v2.0 dataset. The results show that our method has advantages for recognition performance despite large expression variations.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Yan Liang and Yun Zhang "Expression-invariant face recognition using three-dimensional weighted walkthrough and centroid distance," Journal of Electronic Imaging 24(5), 053007 (10 September 2015). https://doi.org/10.1117/1.JEI.24.5.053007
Published: 10 September 2015
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Cited by 1 scholarly publication.
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KEYWORDS
Facial recognition systems

3D modeling

3D image processing

Nose

Statistical analysis

Principal component analysis

3D scanning

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