Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation

This paper addresses the problem of specular surface recovery, and proposes a novel solution based on observing the reflections of a translating planar pattern. Previous works have demonstrated that a specular surface can be recovered from the reflections of two calibrated planar patterns. In this paper, however, only one reference planar pattern is assumed to have been calibrated against a fixed camera observing the specular surface. Instead of introducing and calibrating a second pattern, the reference pattern is allowed to undergo an unknown pure translation, and a closed form solution is derived for recovering such a motion. Unlike previous methods which estimate the shape by directly triangulating the visual rays and reflection rays, a novel method based on computing the projections of the visual rays on the translating pattern is introduced. This produces a depth range for each pixel which also provides a measure of the accuracy of the estimation. The proposed approach enables a simple auto-calibration of the translating pattern, and data redundancy resulting from the translating pattern can improve both the robustness and accuracy of the shape estimation. Experimental results on both synthetic and real data are presented to demonstrate the effectiveness of the proposed approach.

[1]  Michael Lindenbaum,et al.  Dense Mirroring Surface Recovery from 1D Homographies and Sparse Correspondences , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Shree K. Nayar,et al.  A Theory of Specular Surface Geometry , 2004, International Journal of Computer Vision.

[3]  Roberto Cipolla,et al.  Structure and motion from silhouettes , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[4]  Takeo Kanade,et al.  Shape and motion from image streams under orthography: a factorization method , 1992, International Journal of Computer Vision.

[5]  Andrew Blake,et al.  The information available to a moving observer from specularities , 1989, Image and Vision Computing.

[6]  Mads Nielsen,et al.  Computer Vision — ECCV 2002 , 2002, Lecture Notes in Computer Science.

[7]  Pietro Perona,et al.  Local Analysis for 3D Reconstruction of Specular Surfaces - Part II , 2002, ECCV.

[8]  Shree K. Nayar,et al.  Computer Vision - ACCV 2006, 7th Asian Conference on Computer Vision, Hyderabad, India, January 13-16, 2006, Proceedings, Part I , 2006, ACCV.

[9]  Richard Szeliski,et al.  High-accuracy stereo depth maps using structured light , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[10]  Yasushi Yagi Computer Vision - ACCV 2007, 8th Asian Conference on Computer Vision, Tokyo, Japan, November 18-22, 2007, Proceedings, Part I , 2007, ACCV.

[11]  Kiriakos N. Kutulakos,et al.  A theory of inverse light transport , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[12]  Pau Gargallo,et al.  General Specular Surface Triangulation , 2006, ACCV.

[13]  Ohad Ben-Shahar,et al.  A linear formulation of shape from specular flow , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[14]  A. Torralba,et al.  Specular reflections and the perception of shape. , 2004, Journal of vision.

[15]  Michael J. Black,et al.  Specular Flow and the Recovery of Surface Structure , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

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

[17]  Gang Xu,et al.  Dense 3D Reconstruction of Specular and Transparent Objects Using Stereo Cameras and Phase-Shift Method , 2007, ACCV.

[18]  Ohad Ben-Shahar,et al.  Toward a Theory of Shape from Specular Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[19]  P. Perona,et al.  Local analysis for 3D reconstruction of specular surfaces , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[20]  Tim Weyrich,et al.  Dense 3D reconstruction from specularity consistency , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Peter F. Sturm,et al.  Voxel carving for specular surfaces , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.