Photometric Stereo with Small Angular Variations

Most existing successful photometric stereo setups require large angular variations in illumination directions, which results in acquisition rigs that have large spatial extent. For many applications, especially involving mobile devices, it is important that the device be spatially compact. This naturally implies smaller angular variations in the illumination directions. This paper studies the effect of small angular variations in illumination directions to photometric stereo. We explore both theoretical justification and practical issues in the design of a compact and portable photometric stereo device on which a camera is surrounded by a ring of point light sources. We first derive the relationship between the estimation error of surface normal and the baseline of the point light sources. Armed with this theoretical insight, we develop a small baseline photometric stereo prototype to experimentally examine the theory and its practicality.

[1]  Julie Delon,et al.  Small Baseline Stereovision , 2007, Journal of Mathematical Imaging and Vision.

[2]  Robin P. Gardner,et al.  The solid angle subtended at a point by a circular disk , 1969 .

[3]  James J. Clark.  Active photometric stereo , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Fisher Yu,et al.  3D Reconstruction from Accidental Motion , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Mike J. Chantler,et al.  On optimal light configurations in photometric stereo , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[6]  Zhe Wu,et al.  Multi-view Photometric Stereo with Spatially Varying Isotropic Materials , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Ramesh Raskar,et al.  Multiflash Stereopsis: Depth-Edge-Preserving Stereo with Small Baseline Illumination , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Berthold K. P. Horn.  SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .

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

[10]  Neel Joshi,et al.  Micro-Baseline Stereo , 2014 .

[11]  Yasuyuki Matsushita,et al.  A hand-held photometric stereo camera for 3-D modeling , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[12]  Berthold K. P. Horn,et al.  Determining Shape and Reflectance Using Multiple Images , 1978 .

[13]  Ramesh Raskar,et al.  Non-photorealistic camera: depth edge detection and stylized rendering using multi-flash imaging , 2004, SIGGRAPH 2004.

[14]  Björn Stenger,et al.  Non-rigid Photometric Stereo with Colored Lights , 2007, 2007 IEEE 11th International Conference on Computer Vision.

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

[16]  Andrew Jones,et al.  Head-Mounted Photometric Stereo for Performance Capture , 2011, CVMP.

[17]  Jovan Popović,et al.  Dynamic shape capture using multi-view photometric stereo , 2009, SIGGRAPH 2009.

[18]  Jian Guo Liu,et al.  Sub-Pixel Stereo-Matching for DEM Generation from Narrow Baseline Stereo Imagery , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[19]  Sim Heng Ong,et al.  Auto-calibrating photometric stereo using ring light constraints , 2013, Machine Vision and Applications.

[20]  Edward H. Adelson,et al.  Microgeometry capture using an elastomeric sensor , 2011, SIGGRAPH 2011.

[21]  Ping Tan,et al.  Ring-Light Photometric Stereo , 2010, ECCV.