A Glasses-Occluded Face Recognition Method Based on 3D Face Reconstruction
XIONG Peng-Fei1,2, LIU Chang-Ping1, HUANG Lei1
1.Character Recognition Engineering Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190 2.Graduate University, Chinese Academy of Sciences, Beijing 100049
Abstract The instability of eyeglasses treated as facial features is the primary obstacle in glasses-occluded face recognition. The facial features are easily lost by the existing method while eliminating the influence of instable glasses characteristics. To avoid this problem, a 3D realistic face model reconstruction is applied for virtual face images generation to compensate the instability of the glasses. In the method, the glasses are set as an inherent part of face. 3D face reconstruction increases the feasibility of parameter adjustment for different glasses models. Based on this, various influences of glasses segment on face recognition are analyzed. Also, corresponding solutions to image distortion by lens blur and reflection are carried out. Experiments on CAS-PEAL database demonstrate the improvement of the proposed method on face recognition rate and verify the effectiveness of lens treatment.
[1] Oh H J, Lee K M, Lee S U, et al. Occlusion Invariant Face Recognition Using Selective LNMF Basis Images // Proc of the 7th Asian Conference on Computer Vision. Hyderabad, India, 2006: 120-129 [2] Martinez A M. Recognition of Partially Occluded and/or Imprecisely Localized Faces Using a Probabilistic Approach // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Hilton Head Island, USA, 2000, I: 712-717 [3] Zhang Wenchao, Shan Shiguang, Chen Xilin, et al. Local Gabor Binary Patterns Based on Kullback-Leibler Divergence for Partially Occluded Face Recognition. IEEE Signal Processing Letters, 2007, 11(14): 875-878 [4] Saito Y, Kenmochi Y, Kotani K. Estimation of Eyeglassless Facial Images Using Principal Component Analysis // Proc of the International Conference on Image Processing. Kobe, Japan, 1999, IV: 197-201 [5] Du Cheng, Su Guangda. Eyeglasses Removal from Facial Images. Pattern Recognition Letters, 2005, 26(14): 2215-2220 [6] Park J S, Oh Y H, Ahn S C, et al. Glasses Removal from Facial Image Using Recursive Error Compensation. IEEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27(5): 805-811 [7] Wu Chenyu, Liu Ce, Shum H Y. Automatic Eyeglasses Removal from Face Images. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(3): 322-336 [8] Nielson G M. Scattered Data Modeling. IEEE Computer Graphics and Applications, 1993, 13(1): 60-70 [9] Gao Wen, Shan Shiguang, Chai Xiujuan, et al. Virtual Face Image Generation for Illumination and Pose Insensitive Face Recognition // Proc of the IEEE International Conference on Acoustics, Speech, and Signal Processing.Hong Kong, China, 2003, IV: 776-779 [10] Blanz V, Vetter T, Tubingen G. A Morphable Model for the Synthesis of 3D Faces // Proc of the 26th Annual International Conference on Computer Graphics and Interactive Techniques. Los Angeles, USA, 1999, I: 187-194 [11] Blanz V, Vetter T. Face Recognition Based on Fitting a 3D Morphable Model. IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(9): 1063-1074 [12] Pighin F, Hecker J, Lischinski D, et al. Synthesizing Realistic Facial Expressions from Photographs // Proc of the 33rd International Conference and Exhibition on Computer Graphics and Interactive Techniques. Boston, USA, 1998, I: 75-84 [13] Cootes T F, Taylor C J, Cooper D H, et al. Active Shape Models-Their Training and Their Application. Computer Vision and Image Understanding, 1995, 61(1): 38-59 [14] Teukolsky W, Vetterling S, Flannery W. Numerical Recipes in C++: The Art of Scientific Computing. 2nd Edition. Cambridge, UK: Cambridge University Press, 2002 [15] Phong B T. Illumination for Computer Generated Pictures. Communications of the ACM, 1975, 18(6): 311-317 [16] Gao Wen, Cao Bo, Shan Shiguang, et al. The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations. IEEE Trans on Systems, Man and Cybernetics, 2008, 38(1): 149-161 [17] Turk M, Pentland A. Face Recognition Using Eigenfaces // Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Maui, USA, 1991: 586-591
2011, Vol. 24 
