Facial feature estimation from the local structural diversity of skulls

In forensics, the craniofacial reconstruction is employed as an initialization of the identification from skulls. It is a challenging work to develop such a system due to the ambiguity in the relationship between the shape of the skull and the face. In this paper, we present a facial feature estimation method based on the local structural diversity of skulls. A mapping system between the skull structural measurements and the facial feature shapes is established via a RBF regression model. The PCA subspaces are established for the local facial features and the skull structures. Moreover, we investigate the attribute vector of the facial feature polyhedron and the distance graph of the skull structure as the shape descriptors. The experiments demonstrate the feature outlooks can be estimated feasibly and efficiently.

[1]  Jorge Nocedal,et al.  Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization , 1997, TOMS.

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

[3]  Katrina Archer Craniofacial reconstruction using hierarchical B-Spline interpolation , 1997 .

[4]  P Vanezi,et al.  Facial reconstruction using 3-D computer graphics. , 2000, Forensic science international.

[5]  Hans-Peter Seidel,et al.  Reanimating the dead: reconstruction of expressive faces from skull data , 2003, ACM Trans. Graph..

[6]  Hongbin Zha,et al.  Tissue map based craniofacial reconstruction and facial deformation using RBF network , 2004, Third International Conference on Image and Graphics (ICIG'04).

[7]  Hans-Peter Seidel,et al.  Creating Face Models from Vague Mental Images , 2005, SIGGRAPH '05.

[8]  Paul Suetens,et al.  Craniofacial reconstruction using a combined statistical model of face shape and soft tissue depths: methodology and validation. , 2006, Forensic science international.

[9]  Jake K. Aggarwal,et al.  3D Face Recognition Founded on the Structural Diversity of Human Faces , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Peter H. Tu,et al.  Automatic Face Recognition from Skeletal Remains , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Hongbin Zha,et al.  Creating a face model from an unknown skull based on the tissue map , 2008, 2008 15th IEEE International Conference on Image Processing.