Face identification across different poses and illuminations with a 3D morphable model

We present a novel approach for recognizing faces in images taken from different directions and under different illumination. The method is based on a 3D morphable face model that encodes shape and texture in terms of model parameters, and an algorithm that recovers these parameters from a single image of a face. For face identification, we use the shape and texture parameters of the model that are separated from imaging parameters, such as pose and illumination. In addition to the identity, the system provides a measure of confidence. We report experimental results for more than 4000 images from the publicly available CMU-PIE database.

[1]  James D. Foley,et al.  Fundamentals of interactive computer graphics , 1982 .

[2]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[3]  Peter W. Hallinan,et al.  A deformable model for the recognition of human faces under arbitrary illumination , 1995 .

[4]  Timothy F. Cootes,et al.  Automatic face identification system using flexible appearance models , 1995, Image Vis. Comput..

[5]  Tomaso A. Poggio,et al.  Linear Object Classes and Image Synthesis From a Single Example Image , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

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

[8]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[9]  K. Walker,et al.  View-based active appearance models , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[10]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  H Moon,et al.  Computational and Performance Aspects of PCA-Based Face-Recognition Algorithms , 2001, Perception.

[12]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[13]  Linda G. Shapiro,et al.  Computer and Robot Vision (Volume II) , 2002 .

[14]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[15]  Michael Jones,et al.  Multidimensional Morphable Models: A Framework for Representing and Matching Object Classes , 2004, International Journal of Computer Vision.