Traceable 3D imaging metrology

This paper summarizes the causes of uncertainty in 3D data measurement, some basic theory of 3D imaging that explains the origin of some of these causes, and, describes the properties and performances of a 100 square meter facility to perform research in traceable 3D imaging metrology. Built in 2006, the laboratory space allows accurate measurements of 3D data from devices operating at standoff distances from a few centimeters up to 10 meters. A laminar flow of 20°C air at 50% humidity level is maintained within ±0.1°C. The total volume of air in the lab is changed twice a minute (18000 cfm). This characteristic combined with the air filtering design allows air cleanliness to be exceptionally good (Class 100).

[1]  Martial Hebert,et al.  3-D measurements from imaging laser radars: how good are they? , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[2]  François Blais.  Review of 20 years of range sensor development , 2004, J. Electronic Imaging.

[3]  M. Levoy,et al.  An assessment of laser range measurement on marble surfaces , 2001 .

[4]  Andrew E. Johnson,et al.  Registration and integration of textured 3-D data , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[5]  Marc Rioux.  Color 3D electronic imaging of the surface of the human body , 1994, Optics & Photonics.

[6]  Francois Blais,et al.  Active 3D sensing , 2000 .

[7]  Alan M. Lytle,et al.  Status of the NIST 3D imaging system performance evaluation facility , 2006, SPIE Defense + Commercial Sensing.

[8]  Marc Rioux.  Colour 3-D electronic imaging of the surface of the human body , 1997 .

[9]  Warren H. Stevenson,et al.  Performance characteristics of range sensors utilizing optical triangulation , 1992, Proceedings of the IEEE 1992 National Aerospace and Electronics Conference@m_NAECON 1992.

[10]  Olli Jokinen,et al.  Intrinsic Filtering of Range Images Using a Physically Based Noise Model , 2002 .

[11]  R. Fabio.  From point cloud to surface the modeling and visualization problem , 2003 .

[12]  Fabio Remondino.  From point cloud to surface , 2003 .

[13]  Luc Van Gool,et al.  Recording, modeling and visualization of cultural heritage , 2006 .

[14]  Marc Rioux,et al.  Design Of A Large Depth Of View Three-Dimensional Camera For Robot Vision , 1987 .

[15]  Barry N. Taylor,et al.  Guidelines for Evaluating and Expressing the Uncertainty of Nist Measurement Results , 2017 .

[16]  Jussi Paakkari,et al.  Method for evaluating the performance of range imaging devices , 1993, Other Conferences.

[17]  Martial Hebert,et al.  3D measurements from imaging laser radars: how good are they? , 1992, Image Vis. Comput..

[18]  Geoffrey A. Moore.  Crossing the chasm : marketing and selling high-tech products to mainstream customers , 1999 .

[19]  Sing Bing Kang,et al.  Registration and integration of textured 3-D data , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[20]  S. Lippman,et al.  The Scripps Institution of Oceanography , 1959, Nature.

[21]  David Nitzan,et al.  Three-Dimensional Vision Structure for Robot Applications , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  John G. Fryer,et al.  Applications of 3D Measurements from Images , 2007 .

[23]  A. E. Brain,et al.  The measurement and use of registered reflectance and range data in scene analysis , 1977, Proceedings of the IEEE.