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Proceedings Paper

Effects on facial expression in 3D face recognition
Author(s): Kyong Jin Chang; Kevin W. Bowyer; Patrick J. Flynn
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Paper Abstract

This is the first study to compare the PCA and ICP approaches to 3D face recognition, and to propose a local region approach coping with expression variation in 3D face recognition. A new algorithm for 3D face recognition is proposed for handling expression variation. It uses a surface registration-based technique for 3D face recognition. The proposed method uses a fully automatic approach to use to initialize the 3D matching. Results are presented for gallery and probe datasets of 355 subjects imaged in 3D, with significant time lapse between gallery and probe images of a given subject yielding 3,205 3D models. We find that an ICP-based method performs better than a PCA-based method. The evaluation results show that our proposed new algorithm substantially improves performance in the case of varying facial expression. We also examined subject factors in the proposed method on 3D face models by age and gender.

Paper Details

Date Published: 28 March 2005
PDF: 12 pages
Proc. SPIE 5779, Biometric Technology for Human Identification II, (28 March 2005); doi: 10.1117/12.604171
Show Author Affiliations
Kyong Jin Chang, Univ. of Notre Dame (United States)
Kevin W. Bowyer, Univ. of Notre Dame (United States)
Patrick J. Flynn, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 5779:
Biometric Technology for Human Identification II
Anil K. Jain; Nalini K. Ratha, Editor(s)

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