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Multiresolution approach based on projection matrices

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2009-03-01
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The Optical Society of America
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Active triangulation measurement systems with a rigid geometric configuration are inappropriate tor scanning large objects with low measuring tolerances. The reason is that the ratio between the depth recovery error and the lateral extension is a constant that depends on the geometric setup. As a consequence, measuring large areas with low depth recovery error requires the use of multiresolution techniques. We propose a multiresolution technique based on a camera-projector system previously calibrated. The method consists of changing the camera or projector's parameters in order to increase the system depth sensitivity A subpixel retroprojection error in the self-calibration process and a decrease of approximately one order of magnitude in the depth recovery error can be achieved using the proposed method.
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© 2009 Optical Society of America. We thank the Ministerio de Ciencia y Tecnología of Spain for the financial support of this work given by project DPI2005-03891 and the Spanish Ministry of Education for support under a FPU grant.
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1. J. Pages, J. Salvi, R. Garcia, and C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling”, in Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2003), Vol. 1, pp. 133–138. 2. H. Steinbichler, E. H. Nösekabel, and R. Rösch, “Optical inspection in the production line”, in Fringe 2001—4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 587–592. 3. G. Notni, “360 deg shape measurement with fringe projection—calibration and application”, in Fringe 2001—4th International Workshop on Automatic Processing of Fringe Patterns,W. Osten and W. Jüptner, eds. (Data Science Library, Elsevier, 2001), pp. 311–323. 4. G.Wiora, “High resolution measurement of phase-shift amplitude and numeric object phase calculation”, Proc. SPIE 4117, 289–299 (2000). 5. D. Kayser, T. Bothe, and W. Osten, “Scaled topometry in a multisensor approach”, Opt. Eng. 43, 2469–2477 (2004). 6. P. Andrä, E. Ivanov, and W. Osten, “Scaled topometry—an active measurement approach for wide scale 3D surface inspection”, in Fringe 1997: 3rd International Workshop on Automatic Processing of Fringe Patterns, W. Osten and W. Jüptner, eds. (Akademie-Verlag, 1997), pp. 179–189. 7. D. Kayser, T. Bothe, and W. Osten, “Fault detection in grayvalue images of surfaces on different scales”, Proc. SPIE 3744, 110–117 (1999). 8. W. Osten, P. Andrä, and D. Kayser, “Highly-resolved measurement of extended technical surfaces with scalable topometry”, Tech. Mess. ATM 66, 413–428 (1999). 9. J. Vargas and J. A. Quiroga, “A novel multiresolution approach for an adaptable structured light”, Opt. Eng. 47, 023601 (2008). 10. M. Fiala, “Artag, an improved marker system based on artoolkit”, in National Research Council Publication 47166/ERB-1111 (2004). 11. W. Schereiber and G. Notni, “Theory and arrangements of selfcalibrating whole-body three-dimensional measurement systems using fringe projection technique”, Opt. Eng. 39, 159–169 (2000). 12. S. Y. Chen and Y. F. Li, “Self recalibration of a structured light vision system from a single view”, in Proceedings of the IEEE International Conference on Robotics and Automation, Washington DC, (IEEE, 2002), pp. 2539–2544. 13. Y. F. Lie and Y. Chen, “Automatic recalibration of an active structured light vision system”, IEEE Trans. Robot. Autom. 19, 259–568 (2003). 14. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University, 2004). 15. R. Legarda-Sáenz, T. Bothe, and W. Jüptner, “Accurate procedure for calibration of a structured light system”, Opt. Eng. 43, 464–471 (2004). 16. J. Heikkilä, “Geometrical camera calibration using circular control points”, IEEE Trans. Pattern Anal. Mach. Intell. 22, 1066–1077 (2000). 17. O. Faugueras, Three-Dimensional Computer Vision: A Geometric Viewpoint (MIT, 1993).
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