A photometric approach for estimating normals and tangents

This paper presents a technique for acquiring the shape of real-world objects with complex isotropic and anisotropic reflectance. Our method estimates the local normal and tangent vectors at each pixel in a reference view from a sequence of images taken under varying point lighting. We show that for many real-world materials and a restricted set of light positions, the 2D slice of the BRDF obtained by fixing the local view direction is symmetric under reflections of the halfway vector across the normal-tangent and normal-binormal planes. Based on this analysis, we develop an optimization that estimates the local surface frame by identifying these planes of symmetry in the measured BRDF. As with other photometric methods, a key benefit of our approach is that the input is easy to acquire and is less sensitive to calibration errors than stereo or multi-view techniques. Unlike prior work, our approach allows estimating the surface tangent in the case of anisotropic reflectance. We confirm the accuracy and reliability of our approach with analytic and measured data, present several normal and tangent fields acquired with our technique, and demonstrate applications to appearance editing.

[1]  John Hart,et al.  ACM Transactions on Graphics , 2004, SIGGRAPH 2004.

[2]  Hugues Hoppe,et al.  Design of tangent vector fields , 2007, SIGGRAPH 2007.

[3]  David J. Kriegman,et al.  Toward Reconstructing Surfaces With Arbitrary Isotropic Reflectance : A Stratified Photometric Stereo Approach , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[4]  Jiaya Jia,et al.  Efficient photometric stereo on glossy surfaces with wide specular lobes , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Steven M. Seitz,et al.  Shape and Spatially-Varying BRDFs from Photometric Stereo , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  David J. Kriegman,et al.  Beyond Lambert: reconstructing specular surfaces using color , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[7]  Jonathan Richard Shewchuk,et al.  Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator , 1996, WACG.

[8]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[9]  Pieter Peers,et al.  Rapid Acquisition of Specular and Diffuse Normal Maps from Polarized Spherical Gradient Illumination , 2007 .

[10]  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.

[11]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.

[12]  Philip Dutré,et al.  The Free Form Light Stage , 2002, Rendering Techniques.

[13]  Hans-Peter Seidel,et al.  Realistic, hardware-accelerated shading and lighting , 1999, SIGGRAPH.

[14]  Christophe Schlick,et al.  An Inexpensive BRDF Model for Physically‐based Rendering , 1994, Comput. Graph. Forum.

[15]  Wojciech Matusik,et al.  Inverse shade trees for non-parametric material representation and editing , 2006, ACM Trans. Graph..

[16]  Kristin J. Dana,et al.  Relief texture from specularities , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  James F. Blinn,et al.  Models of light reflection for computer synthesized pictures , 1977, SIGGRAPH.

[18]  Hans-Peter Seidel,et al.  Mesostructure from Specularity , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[19]  Philippe Bekaert,et al.  High quality mesostructure acquisition using specularities , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Peter Shirley,et al.  A microfacet-based BRDF generator , 2000, SIGGRAPH.

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

[22]  Frédo Durand,et al.  Experimental analysis of BRDF models , 2005, EGSR '05.

[23]  Steven M. Seitz,et al.  Shape and materials by example: a photometric stereo approach , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

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

[25]  David J. Kriegman,et al.  Photometric stereo with non-parametric and spatially-varying reflectance , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

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

[27]  Donald P. Greenberg,et al.  A comprehensive physical model for light reflection , 1991, SIGGRAPH.

[28]  Szymon Rusinkiewicz,et al.  A New Change of Variables for Efficient BRDF Representation , 1998, Rendering Techniques.

[29]  Szymon Rusinkiewicz,et al.  Illustration of complex real-world objects using images with normals , 2007, NPAR '07.

[30]  Rui J. P. de Figueiredo,et al.  A Theory of Photometric Stereo for a Class of Diffuse Non-Lambertian Surfaces , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Ramesh Raskar,et al.  Fast separation of direct and global components of a scene using high frequency illumination , 2006, ACM Trans. Graph..

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

[33]  Robert L. Cook,et al.  A Reflectance Model for Computer Graphics , 1987, TOGS.

[34]  Marc Olano,et al.  Reflection space image based rendering , 1999, SIGGRAPH.

[35]  James Arvo,et al.  Barycentric parameterizations for isotropic BRDFs , 2005, IEEE Transactions on Visualization and Computer Graphics.