Shape from shading for hybrid surfaces as applied to tooth reconstruction

Accurate 3-D modeling of the human teeth helps patients avoid the discomfort of the mold process, and improves the data accuracy for oral surgeons, orthodontists and dental care personnel. Since the surface of the human tooth is almost textureless, Shape from Shading (SFS) has been successfully adopted in solving this problem. This paper evaluates 3-D tooth reconstruction using three SFS models. Based on quantitative error analysis and curvature analysis using Robust Point Matching (RPM) and visualization results, the assumption of a perspective camera projection and an Oren-Nayar reflectance model has been proved to be the most ideal for extracting crown information from an image of a human tooth. Three reconstructed teeth have been shown to demonstrate the performance of this model.

[1]  Anand Rangarajan,et al.  A new point matching algorithm for non-rigid registration , 2003, Comput. Vis. Image Underst..

[2]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.

[3]  S. Osher,et al.  Lax-Friedrichs sweeping scheme for static Hamilton-Jacobi equations , 2004 .

[4]  Berthold K. P. Horn.  Obtaining shape from shading information , 1989 .

[5]  Shree K. Nayar,et al.  Generalization of the Lambertian model and implications for machine vision , 1995, International Journal of Computer Vision.

[6]  C.-C. Jay Kuo,et al.  Shape from Shading with a Generalized Reflectance Map Model , 1997, Comput. Vis. Image Underst..

[7]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[8]  Berthold K. P. Horn.  SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .

[9]  Aly A. Farag,et al.  A New Formulation for Shape from Shading for Non-Lambertian Surfaces , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[10]  Olivier D. Faugeras,et al.  Shape from shading: a well-posed problem? , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).