3D model-based pose invariant face recognition from multiple views

A 3D model-based pose invariant face recognition method that can recognise a human face from its multiple views is proposed. First, pose estimation and 3D face model adaptation are achieved by means of a three-layer linear iterative process. Frontal view face images are synthesised using the estimated 3D models and poses. Then the discriminant ‘waveletfaces’ are extracted from these synthesised frontal view images. Finally, corresponding nearest feature space classifier is implemented. Experimental results show that the proposed method can recognise faces under variable poses with good accuracy.

[1]  Parke,et al.  Parameterized Models for Facial Animation , 1982, IEEE Computer Graphics and Applications.

[2]  Xinhua Zhuang,et al.  Pose estimation from corresponding point data , 1989, IEEE Trans. Syst. Man Cybern..

[3]  George Wolberg,et al.  Digital image warping , 1990 .

[4]  David G. Lowe,et al.  Fitting Parameterized Three-Dimensional Models to Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Chung-Lin Huang,et al.  Human Face Recognition from A Single Front View , 1992, Int. J. Pattern Recognit. Artif. Intell..

[6]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Hiroshi Murase,et al.  Learning and recognition of 3D objects from appearance , 1993, [1993] Proceedings IEEE Workshop on Qualitative Vision.

[8]  Alex Pentland,et al.  View-based and modular eigenspaces for face recognition , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[9]  R. Schaback.  Creating Surfaces from Scattered Data Using Radial Basis Functions , 1995 .

[10]  Rama Chellappa,et al.  Human and machine recognition of faces: a survey , 1995, Proc. IEEE.

[11]  Thomas Fromherz,et al.  Face Recognition: a Summary of 1995 - 1997 , 1997 .

[12]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[13]  Sun-Yuan Kung,et al.  Face recognition/detection by probabilistic decision-based neural network , 1997, IEEE Trans. Neural Networks.

[14]  Jun Zhang,et al.  Pace recognition: eigenface, elastic matching, and neural nets , 1997, Proc. IEEE.

[15]  Hong Yan,et al.  An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Kin Hong Wong,et al.  An efficient iterative pose estimation algorithm , 1998, Image Vis. Comput..

[17]  Olivier Y. de Vel,et al.  Line-Based Face Recognition under Varying Pose , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Stan Z. Li,et al.  Face recognition using the nearest feature line method , 1999, IEEE Trans. Neural Networks.

[19]  Tsuhan Chen,et al.  Pose invariant face recognition , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[20]  Gregory D. Hager,et al.  Fast and Globally Convergent Pose Estimation from Video Images , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Pong C. Yuen,et al.  Recognition of head-and-shoulder face image using virtual frontal-view image , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[22]  M. A. Grudin,et al.  On internal representations in face recognition systems , 2000, Pattern Recognit..

[23]  Haiyuan Wu,et al.  Head pose estimation using both color and feature information , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[24]  Lale Akarun,et al.  Two-stage approach for pose invariant face recognition , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[25]  Alex Pentland,et al.  Looking at People: Sensing for Ubiquitous and Wearable Computing , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  S. C. Hui,et al.  Fast face identification under varying pose from a single 2-D model view , 2001 .

[27]  Sami Romdhani,et al.  Face identification across different poses and illuminations with a 3D morphable model , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[28]  Marian Stewart Bartlett,et al.  Face recognition by independent component analysis , 2002, IEEE Trans. Neural Networks.

[29]  Jen-Tzung Chien,et al.  Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Fernand S. Cohen,et al.  3-D face structure extraction and recognition from images using 3-D morphing and distance mapping , 2002, IEEE Trans. Image Process..

[31]  Konstantinos N. Plataniotis,et al.  Face recognition using kernel direct discriminant analysis algorithms , 2003, IEEE Trans. Neural Networks.

[32]  Thomas Vetter,et al.  Face Recognition Based on Fitting a 3D Morphable Model , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Kostas Daniilidis,et al.  Linear Pose Estimation from Points or Lines , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Jian Yao,et al.  Efficient model-based linear head motion recovery from movies , 2004, CVPR 2004.

[35]  Shizuo Sakamoto,et al.  An appearance model constructed on 3-D surface for robust face recognition against pose and illumination variations , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).