Piecewise single view Photometric Stereo with multi-view constraints

This paper presents a novel Photometric Stereo approach for static views that recasts the problem into a piecewise formulation. The proposed algorithm, called Piecewise Photometric Stereo (PPS), entails several advantages in respect to previous global approaches. It is intrinsically more efficient, since reconstructing the surface in patches is computationally faster than reconstructing the global surface. Each patch has been associated an individual photometric model rather than a single global model as used in classical approaches. In this way, the piecewise formulation may grasp more complex lighting effects. Finally, the global metric properties of the shape is preserved using the multi-view constraints. In this pipeline, structure from motion is exploited to define such set of constraints and to compose a 3D mesh representing the metric structure of the object. Real results with ground truth show the positive performance of our algorithm compared with a classical global approach for Photometric Stereo.

[1]  Olivier D. Faugeras,et al.  Shape From Shading , 2006, Handbook of Mathematical Models in Computer Vision.

[2]  H. Opower Multiple view geometry in computer vision , 2002 .

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

[4]  Henrik Aanæs,et al.  Interesting Interest Points , 2011, International Journal of Computer Vision.

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

[6]  Marc Pollefeys,et al.  Multiple view geometry , 2005 .

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

[8]  Alessio Del Bue,et al.  Bilinear Modeling via Augmented Lagrange Multipliers (BALM) , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Yasuyuki Matsushita,et al.  High-quality shape from multi-view stereo and shading under general illumination , 2011, CVPR 2011.

[10]  Ronen Basri,et al.  Photometric stereo with general, unknown lighting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[11]  Nikos Paragios,et al.  Handbook of Mathematical Models in Computer Vision , 2005 .

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

[13]  David J. Kriegman,et al.  Shape from Varying Illumination and Viewpoint , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[14]  Saïda Bouakaz,et al.  Shape From Silhouette: Towards a Solution for Partial Visibility Problem , 2006, Eurographics.

[15]  Narendra Ahuja,et al.  Shape From Texture: Integrating Texture-Element Extraction and Surface Estimation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Stefano Soatto,et al.  A geometric approach to shape from defocus , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.