Surface Reconstruction in Photometric Stereo with Calibration Error

A method is described for surface reconstruction that accounts for the calibration errors in photometric stereo. The angular errors in calibrated light directions due to noise cause errors in surface normal estimates. Investigation of the effect of these calibration errors on the surface normals revealed that errors in the estimated light directions and in the surface normal estimates follow a Fisher distribution. By accounting for the Fisher noise in surface normals, the proposed method reconstructs a surface using maximum likelihood estimation. Extensive comparison with previous methods using synthetic and real scenes demonstrated that the proposed method outperforms them in the presence of calibration errors.

[1]  Rama Chellappa,et al.  Direct Analytical Methods for Solving Poisson Equations in Computer Vision Problems , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[3]  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..

[4]  B. Karacali,et al.  Partial integrability in surface reconstruction from a given gradient field , 2002, Proceedings. International Conference on Image Processing.

[5]  M. R. Celis A TRUST REGION STRATEGY FOR NONLINEAR EQUALITY CONSTRAINED OPTIMIZATION (NONLINEAR PROGRAMMING, SEQUENTIAL QUADRATIC) , 1985 .

[6]  Rama Chellappa,et al.  What Is the Range of Surface Reconstructions from a Gradient Field? , 2006, ECCV.

[7]  John Harris,et al.  Handbook of mathematics and computational science , 1998 .

[8]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[9]  Masaru Kono,et al.  Statistics of paleomagnetic inclination data , 1980 .

[10]  Edwin R. Hancock,et al.  Combinatorial Surface Integration , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[11]  Rama Chellappa,et al.  A Method for Enforcing Integrability in Shape from Shading Algorithms , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  R. Fisher Dispersion on a sphere , 1953, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[13]  Peter Kovesi,et al.  Shapelets correlated with surface normals produce surfaces , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[14]  H. Schaeben,et al.  PARAMETERIZATIONS AND PROBABILITY DISTRIBUTIONS OF ORIENTATIONS , 1990 .