Pose invariant face recognition with 3D morphable model and neural network

This paper introduces a pose invariant face recognition method with a training image and a query image using 3D morphable model and neural network. Our system uses 3D morphable model to get the reconstructed 3D face from the training image and obtains 2D image patches of facial components from the 3D face under varying head pose. The 2D image patches are used to train a neural network for pose invariant face recognition. Because those patches are obtained from the varying head pose, the neural network has robustness in the query image under the different head pose form the training image. Our pose invariant face recognition system has the performance of correct recognition higher than 98% with BJUT 3D scan database.

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

[2]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Yee Whye Teh,et al.  Names and faces in the news , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[4]  Volker Blanz,et al.  Component-Based Face Recognition with 3D Morphable Models , 2003, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[5]  Alan F. Murray,et al.  International Joint Conference on Neural Networks , 1993 .

[6]  Thomas Vetter,et al.  A morphable model for the synthesis of 3D faces , 1999, SIGGRAPH.

[7]  Chengjun Liu,et al.  A Bayesian Discriminating Features Method for Face Detection , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Cordelia Schmid,et al.  IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2004, Washington, DC, USA, June 27 - July 2, 2004 , 2004, CVPR Workshops.

[9]  Takeo Kanade,et al.  Object Detection Using the Statistics of Parts , 2004, International Journal of Computer Vision.

[10]  Lei Zhang,et al.  Face synthesis and recognition from a single image under arbitrary unknown lighting using a spherical harmonic basis morphable model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[11]  Ralph Gross,et al.  Appearance-based face recognition and light-fields , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.