A hand-held photometric stereo camera for 3-D modeling

This paper presents a simple yet practical 3-D modeling method for recovering surface shape and reflectance from a set of images. We attach a point light source to a hand-held camera to add a photometric constraint to the multi-view stereo problem. Using the photometric constraint, we simultaneously solve for shape, surface normal, and reflectance. Unlike prior approaches, we formulate the problem using realistic assumptions of a near light source, non-Lambertian surfaces, perspective camera model, and the presence of ambient lighting. The effectiveness of the proposed method is verified using simulated and real-world scenes.

[1]  Li Zhang,et al.  Shape and motion under varying illumination: unifying structure from motion, photometric stereo, and multiview stereo , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[2]  Thomas Malzbender,et al.  Surface enhancement using real-time photometric stereo and reflectance transformation , 2006, EGSR '06.

[3]  Roberto Cipolla,et al.  Multiview Photometric Stereo , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Szymon Rusinkiewicz,et al.  Efficiently combining positions and normals for precise 3D geometry , 2005, ACM Trans. Graph..

[5]  David J. Kriegman,et al.  ShadowCuts: Photometric Stereo with Shadows , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

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

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

[8]  Atsuto Maki,et al.  Geotensity: Combining Motion and Lighting for 3D Surface Reconstruction , 2004, International Journal of Computer Vision.

[9]  Ronen Basri,et al.  Dense shape reconstruction of a moving object under arbitrary, unknown lighting , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[10]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[11]  Michael A. Saunders,et al.  LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares , 1982, TOMS.

[12]  Maria Petrou,et al.  The 4-Source Photometric Stereo Technique for Three-Dimensional Surfaces in the Presence of Highlights and Shadows , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[14]  Vladimir Kolmogorov,et al.  An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Reinhard Koch,et al.  Visual Modeling with a Hand-Held Camera , 2004, International Journal of Computer Vision.

[16]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[17]  Richard Szeliski,et al.  High-quality video view interpolation using a layered representation , 2004, SIGGRAPH 2004.

[18]  M. Gross,et al.  Analysis of human faces using a measurement-based skin reflectance model , 2006, ACM Trans. Graph..

[19]  Vladimir Kolmogorov,et al.  What energy functions can be minimized via graph cuts? , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Martin Jägersand,et al.  Variational Shape and Reflectance Estimation Under Changing Light and Viewpoints , 2006, ECCV.

[21]  Michael Goesele,et al.  Multi-View Stereo Revisited , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[22]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[23]  David J. Kriegman,et al.  Passive photometric stereo from motion , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[24]  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).