Facial feature extraction using topological methods

Automatic facial feature extraction is one of the most important and attempted problems in computer vision. It is a necessary step in face recognition, facial image compression and low-bit video coding. The methodology presented in this paper, considers the facial image as a surface. Topological properties of the facial surface, such as principal curvatures are used to extract the eyes and mouth, which form deep valleys on the surface. Ravines are points on the surface where the maximum curvature is a local maximum in the corresponding principal direction. The basic idea of the proposed method is to model the facial features as ravines on the facial surface. Experimental results have shown accurate extraction of the eye boundaries and the mouth opening in a very small computational time.

[1]  A. Gray Modern Differential Geometry of Curves and Surfaces , 1993 .

[2]  Tosiyasu L. Kunii,et al.  Parallel algorithms for extracting ridges and ravines , 1995, Proceedings the First Aizu International Symposium on Parallel Algorithms/Architecture Synthesis.

[3]  King Ngi Ngan,et al.  Face segmentation using skin-color map in videophone applications , 1999, IEEE Trans. Circuits Syst. Video Technol..

[4]  Olivier Monga,et al.  Thin Nets and Crest Lines: Application to Satellite Data and Medical Images , 1997, Comput. Vis. Image Underst..

[5]  Olivier Monga,et al.  Thin nets and crest lines: application to satellite data and medical images , 1995, Proceedings., International Conference on Image Processing.

[6]  Hamid Krim,et al.  Compression and transmission of facial images over very narrowband wireless channels , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[7]  Ramesh C. Jain,et al.  Invariant surface characteristics for 3D object recognition in range images , 1985, Comput. Vis. Graph. Image Process..

[8]  Tosiyasu L. Kunii,et al.  Hierarchic shape description via singularity and multiscaling , 1994, Proceedings Eighteenth Annual International Computer Software and Applications Conference (COMPSAC 94).

[9]  A. Ben Hamza,et al.  A topological variational model for image singularities , 2002, Proceedings. International Conference on Image Processing.

[10]  Gaile G. Gordon,et al.  Face recognition based on depth maps and surface curvature , 1991, Optics & Photonics.

[11]  Aysegul Gunduz Compression and Transmission of Facial Images Over Very Narrowband Channels , 2003 .