Self-calibrating photometric stereo

We present a self-calibrating photometric stereo method. From a set of images taken from a fixed viewpoint under different and unknown lighting conditions, our method automatically determines a radiometric response function and resolves the generalized bas-relief ambiguity for estimating accurate surface normals and albedos. We show that color and intensity profiles, which are obtained from registered pixels across images, serve as effective cues for addressing these two calibration problems. As a result, we develop a complete auto-calibration method for photometric stereo. The proposed method is useful in many practical scenarios where calibrations are difficult. Experimental results validate the accuracy of the proposed method using various real-world scenes.

[1]  Shree K. Nayar,et al.  Modeling the space of camera response functions , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Heung-Yeung Shum,et al.  Radiometric calibration from a single image , 2004, CVPR 2004.

[3]  M. Werman,et al.  Color lines: image specific color representation , 2004, CVPR 2004.

[4]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[5]  Ondrej Drbohlav,et al.  Specularities Reduce Ambiguity of Uncalibrated Photometric Stereo , 2002, ECCV.

[6]  Shree K. Nayar,et al.  Determining the Camera Response from Images: What Is Knowable? , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  David J. Kriegman,et al.  Resolving the Generalized Bas-Relief Ambiguity by Entropy Minimization , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Mike J. Chantler,et al.  Can two specular pixels calibrate photometric stereo? , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[9]  Takahiro Okabe,et al.  Attached shadow coding: Estimating surface normals from shadows under unknown reflectance and lighting conditions , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[10]  David J. Kriegman,et al.  Isotropy, Reciprocity and the Generalized Bas-Relief Ambiguity , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

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

[12]  William T. Freeman,et al.  Understanding belief propagation and its generalizations , 2003 .

[13]  Shree K. Nayar,et al.  Radiometric self calibration , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[14]  Takahiro Okabe,et al.  Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[15]  Todd E. Zickler,et al.  A projective framework for radiometric image analysis , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Yasuyuki Matsushita,et al.  Radiometric calibration using temporal irradiance mixtures , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

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

[18]  Stephen Lin,et al.  Determining the radiometric response function from a single grayscale image , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[19]  Marc Pollefeys,et al.  Radiometric alignment of image sequences , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[20]  David J. Kriegman,et al.  Reflections on the generalized bas-relief ambiguity , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[21]  Athinodoros S. Georghiades,et al.  Incorporating the Torrance and Sparrow model of reflectance in uncalibrated photometric stereo , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[22]  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.

[23]  Daniel Snow,et al.  Determining Generative Models of Objects Under Varying Illumination: Shape and Albedo from Multiple Images Using SVD and Integrability , 1999, International Journal of Computer Vision.

[24]  Srinivasa G. Narasimhan,et al.  Clustering Appearance for Scene Analysis , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

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