Specularities Reduce Ambiguity of Uncalibrated Photometric Stereo

Lambertian photometric stereo with uncalibrated light directions and intensities determines the surface normals only up to an invertible linear transformation. We show that if object reflectance is a sum of Lambertian and specular terms, the ambiguity reduces into a 2dof group of transformations (compositions of isotropic scaling, rotation around the viewing vector, and change in coordinate frame handedness).Such ambiguity reduction is implied by the consistent viewpoint constraint which requires that all lights reflected around corresponding specular normals must give the same vector (the viewing direction). To employ the constraint, identification of specularities in images corresponding to four different point lights in general configuration suffices. When the consistent viewpoint constraint is combined with integrability constraint, binary convex/concave ambiguity composed with isotropic scaling results. The approach is verified experimentally.We observe that an analogical result applies to the case of uncalibrated geometric stereo with four affine cameras in a general configuration observing specularities from a single distant point light source.

[1]  Andrea J. van Doorn,et al.  The Generic Bilinear Calibration-Estimation Problem , 2004, International Journal of Computer Vision.

[2]  Katsushi Ikeuchi,et al.  Extracting the Shape and Roughness of Specular Lobe Objects Using Four Light Photometric Stereo , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Alan L. Yuille,et al.  The KGBR viewpoint-lighting ambiguity and its resolution by generic constraints , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[4]  Sang Wook Lee,et al.  Estimation of diffuse and specular appearance , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[5]  Richard Szeliski,et al.  Vision Algorithms: Theory and Practice , 2002, Lecture Notes in Computer Science.

[6]  David J. Kriegman,et al.  Illumination cones for recognition under variable lighting: faces , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[7]  E. North Coleman,et al.  Obtaining 3-dimensional shape of textured and specular surfaces using four-source photometry , 1982, Comput. Graph. Image Process..

[8]  Hideki Hayakawa Photometric stereo under a light source with arbitrary motion , 1994 .

[9]  Lawrence B. Wolff,et al.  Surface Curvature and Shape Reconstruction from Unknown Multiple Illumination and Integrability , 1997, Comput. Vis. Image Underst..

[10]  Takeo Kanade,et al.  Determining shape and reflectance of hybrid surfaces by photometric sampling , 1989, IEEE Trans. Robotics Autom..

[11]  Andrew W. Fitzgibbon,et al.  Bundle Adjustment - A Modern Synthesis , 1999, Workshop on Vision Algorithms.

[12]  Daniel Snow,et al.  Shape and albedo from multiple images using integrability , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  O. Drbohlav,et al.  Unambiguous determination of shape from photometric stereo with unknown light sources , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

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

[15]  David W. Jacobs,et al.  Linear fitting with missing data: applications to structure-from-motion and to characterizing intensity images , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[16]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 2004, International Journal of Computer Vision.