A Novel Expression Deformation Model for 3D Face Recognition

Chuanjun WANG  Li LI  Xuefeng BAI  Xiamu NIU  

IEICE TRANSACTIONS on Information and Systems   Vol.E95-D   No.12   pp.3113-3116
Publication Date: 2012/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E95.D.3113
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
3D face recognition,  expression deformation modeling,  Fourier series,  PCA,  

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The accuracy of non-rigid 3D face recognition is highly influenced by the capability to model the expression deformations. Given a training set of non-neutral and neutral 3D face scan pairs from the same subject, a set of Fourier series coefficients for each face scan is reconstructed. The residues on each frequency of the Fourier series between the finely aligned pairs contain the expression deformation patterns and PCA is applied to learn these patterns. The proposed expression deformation model is then built by the eigenvectors with top eigenvalues from PCA. Recognition experiments are conducted on a 3D face database that features a rich set of facial expression deformations, and experimental results demonstrate the feasibility and merits of the proposed model.