Strategies and Benefits of Fusion of 2D and 3D Face Recognition

The extension of 2D image-based face recognition methods with respect to 3D shape information and the fusion of both modalities is one of the main topics in the recent development of facial recognition. In this paper we discuss different strategies and their expected benefit for the fusion of 2D and 3D face recognition. The face recognition grand challenge (FRGC) provides for the first time ever a public benchmark dataset of a suitable size to evaluate the accuracy of both 2D and 3D face recognition. We use this benchmark to evaluate hierarchical graph matching (HGM), an universal approach to 2D and 3D face recognition, and demonstrate the benefit of different fusion strategies. The results show that HGM yields the best results presented at the recent FRGC workshop, that 2D face recognition is significantly more accurate than 3D face recognition and that the fusion of both modalities leads to a further improvement of the 2D results.

[1]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[2]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

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

[5]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Department of Electrical,et al.  Computational and Performance Aspects of PCA-Based Face-Recognition Algorithms , 2001, Perception.

[7]  J. L. Wayman,et al.  Best practices in testing and reporting performance of biometric devices. , 2002 .

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

[9]  Bruce A. Draper,et al.  The CSU Face Identification Evaluation System: Its Purpose, Features, and Structure , 2003, ICVS.

[10]  Patrick J. Flynn,et al.  Face Recognition Using 2D and 3D Facial Data , 2003 .

[11]  Patrick J. Flynn,et al.  A Survey Of 3D and Multi-Modal 3D+2D Face Recognition , 2004 .

[12]  Patrick J. Flynn,et al.  Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).