Heliometric Stereo: Shape from Sun Position, Proceedings of the 12 th European Conference on Computer Vision, pp.357-370, 2012. ,
DOI : 10.1007/978-3-642-33709-3_26
Photometric stereo for outdoor webcams, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.262-269, 2012. ,
DOI : 10.1109/CVPR.2012.6247684
Resolving the Generalized Bas-Relief Ambiguity by Entropy Minimization, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007. ,
DOI : 10.1109/CVPR.2007.383208
Alternating Proximal Algorithms for Weakly Coupled Convex Minimization Problems. Applications to Dynamical Games and PDE's, Journal of Convex Analysis, vol.15, issue.3, pp.485-506, 2008. ,
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations, Applied Mathematical Sciences, 2006. ,
The 4-source photometric stereo technique for three-dimensional surfaces in the presence of highlights and shadows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.10, pp.1239-1252, 2003. ,
DOI : 10.1109/TPAMI.2003.1233898
The bas-relief ambiguity, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.33-44, 1999. ,
DOI : 10.1109/CVPR.1997.609461
Fast dual minimization of the vectorial total variation norm and applications to color image processing, Inverse Problems and Imaging, vol.2, issue.4, pp.455-484, 2008. ,
DOI : 10.3934/ipi.2008.2.455
An Algorithm for Total Variation Minimization and Applications, Journal of Mathematical Imaging and Vision, vol.20, issue.1, pp.89-97, 2004. ,
Image recovery via total variation minimization and related problems, Numerische Mathematik, vol.76, issue.2, pp.167-188, 1997. ,
DOI : 10.1007/s002110050258
A First-Order Primal-Dual Algorithm for Convex Problems with??Applications to Imaging, Journal of Mathematical Imaging and Vision, vol.60, issue.5, pp.120-145, 2011. ,
DOI : 10.1007/s10851-010-0251-1
URL : https://hal.archives-ouvertes.fr/hal-00490826
Reflections on the Generalized Bas-Relief Ambiguity, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.788-795, 2005. ,
DOI : 10.1109/CVPR.2005.299
Multiview normal field integration using level set methods, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007. ,
DOI : 10.1109/CVPR.2007.383357
Can two specular pixels calibrate photometric stereo?, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1850-1857, 2005. ,
DOI : 10.1109/ICCV.2005.53
Numerical methods for shape-from-shading: A new survey with benchmarks, Computer Vision and Image Understanding, vol.109, issue.1, pp.22-43, 2007. ,
DOI : 10.1016/j.cviu.2007.09.003
Learning and Recognizing Objects Using Illumination Subspaces, Proceedings of the 4 th European Conference on Computer Vision, International Workshop on Object Representation for Computer Vision, 1996. ,
Surface Curvature and Shape Reconstruction from Unknown Multiple Illumination and Integrability, Computer Vision and Image Understanding, vol.65, issue.2, pp.347-359, 1997. ,
DOI : 10.1006/cviu.1996.0581
A closed-form solution to uncalibrated photometric stereo via diffuse maxima, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.821-828, 2012. ,
DOI : 10.1109/CVPR.2012.6247754
A method for enforcing integrability in shape from shading algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.10, issue.4, pp.439-451, 1988. ,
DOI : 10.1109/34.3909
Generalised Perspective Shape from Shading in Spherical Coordinates, Proceedings of the 4 th International Conference on Scale Space and Variational Methods in Computer Vision, pp.222-233, 2013. ,
DOI : 10.1007/978-3-642-38267-3_19
Incorporating the Torrance and Sparrow model of reflectance in uncalibrated photometric stereo, Proceedings Ninth IEEE International Conference on Computer Vision, pp.816-823, 2003. ,
DOI : 10.1109/ICCV.2003.1238432
From few to many: illumination cone models for face recognition under variable lighting and pose, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.6, pp.643-660, 2001. ,
DOI : 10.1109/34.927464
Least squares surface reconstruction from measured gradient fields Photometric stereo under a light-source with arbitrary motion, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 25. Hayakawa H, pp.113079-3089, 1994. ,
Multiview Photometric Stereo, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.3, pp.548-554, 2008. ,
DOI : 10.1109/TPAMI.2007.70820
Example-based photometric stereo: shape reconstruction with general, varying BRDFs, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.8, pp.1254-1264, 2005. ,
DOI : 10.1109/TPAMI.2005.158
The variational approach to shape from shading, Computer Vision, Graphics, and Image Processing, vol.33, issue.2, pp.174-208, 1986. ,
DOI : 10.1016/0734-189X(86)90114-3
Shape from Shading, 1989. ,
Depth from gradient fields and control points: bias correction in photometric stereo, Image and Vision Computing, vol.22, issue.9, pp.681-694, 2004. ,
DOI : 10.1016/j.imavis.2004.01.005
The generic bilinear calibration-estimation problem, International Journal of Computer Vision, vol.23, issue.3, pp.217-234, 1997. ,
DOI : 10.1023/A:1007971132346
Existence and uniqueness in photometric stereo, Applied Mathematics and Computation, vol.44, issue.1, pp.1-103, 1991. ,
DOI : 10.1016/0096-3003(91)90001-4
Acquiring Linear Subspaces for Face Recognition under Variable Lighting, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.5, pp.684-698, 2005. ,
Beyond Lambert: Reconstructing Specular Surfaces Using Color, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.286-295, 2005. ,
DOI : 10.1109/CVPR.2005.88
Perspective Photometric Stereo with Shadows, Proceedings of the 4 th International Conference on Scale Space and Variational Methods in Computer Vision, pp.258-269, 2013. ,
DOI : 10.1007/978-3-642-38267-3_22
Uniqueness in shape from shading, International Journal of Computer Vision, vol.15, issue.1, pp.75-104, 1991. ,
DOI : 10.1007/BF00128151
Integrability disambiguates surface recovery in two-image photometric stereo, International Journal of Computer Vision, vol.17, issue.1, pp.105-113, 1990. ,
DOI : 10.1007/BF00056773
A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima, International Journal of Computer Vision, vol.49, issue.2???3, 2013. ,
DOI : 10.1007/s11263-013-0665-5
Illumination for computer generated pictures, Communications of the ACM, vol.18, issue.6, pp.311-317, 1975. ,
DOI : 10.1145/360825.360839
Solving the Uncalibrated Photometric Stereo Problem Using Total Variation, Proceedings of the 4 th International Conference on Scale Space and Variational Methods in Computer Vision, pp.270-281, 2013. ,
DOI : 10.1007/978-3-642-38267-3_23
Enforcing integrability by error correction using L1- minimization Nonlinear Total Variation Based Noise Removal Algorithms, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 43. Rudin LI, pp.1-4259, 1992. ,
Direct analytical methods for solving Poisson equations in computer vision problems, Self-calibrating Photometric Stereo. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 45, pp.435-446, 1990. ,
Photometric stereo with coherent outlier handling and confidence estimation Photometric Method for Determining Surface Orientation from Multiple Images, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 47, pp.139-144, 1980. ,
Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery, Proceedings of the 10 th Asian Conference on Computer Vision, 2010. ,
DOI : 10.1145/965161.806819
Shape and albedo from multiple images using integrability, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.158-164, 1997. ,
DOI : 10.1109/CVPR.1997.609314
Multi-view Photometric Stereo with Spatially Varying Isotropic Materials, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013. ,
DOI : 10.1109/CVPR.2013.195