Abstract
Even though stereo-DIC is widely used in the field of experimental mechanics, uncertainty quantification techniques lag behind. Camera motion for example is often neglected, even though it is present and it can introduce bias. We propose to estimate the error caused by camera motion, based on the epipolar distance, by using a 3-camera system. This solves the problem of the lack of sensitivity along the epipolar line by placing a third camera perpendicular, providing sensitivity in both directions. The third camera provides modest improvement on the results with an optimized triangulation.
References
Blaysat B, Grediac M, Sur F (2016) Effect of interpolation in noise propagation from images to dic displacement maps. Int J Numer Methods Eng 108:213–232
Gao Z, Xu X, Su Y, Zang Q (2016) Experimental analysis of image noise and interpolation bias in digital image correlation. Opt Lasers Eng 81:46–53
Blaysat B, Grediac M, Sur F (2016) On the propagation of camera sensor noise to displacement maps obtained by dic - an experimental study. Exp Mech 56(6):919–944
Bomarito GF, Hochhalter JD, Ruggles TJ, Cannon AH (2017) Increasing accuracy and precision of digital image correlation through pattern optimization. Opt Lasers Eng 91:73–85
Iadicola MA (2016) Uncertainties of digital image correlation due to pattern degradation at large strain. Advancement of Optical Methods in Experimental Mechanics 3:247–253
Lavatelli A, Zappa E (2017) A displacement uncertainty model for 2-d dic measurement under motion blur conditions. IEEE Trans Instrum Meas 66(3):451–459
Iadicola MA, Creuziger AA (2015) Uncertainties of digital image correlation near strain localizations. Advancement of Optical Methods in Experimental Mechanics 3:277–285
Pan B, Shi W, Lubineau G (2015) Effect of camera temperature variations on stereo-digital image correlation measurements. Appl Opt 34:54
Balcaen R, Reu P, Lava P, Debruyne D (2017) Evaluation of camera motion in stereo-dic. International Digital Imaging Correlation Society 1–3
Balcaen R, Wittevrongel L, Reu P, Lava P, Debruyne D (2017) Stereo-dic calibration and speckle image generator based on fe formulations. Exp Mech 57(5):703–718
Balcaen R, Reu P, Lava P, Debruyne D (2016) Stereo-dic uncertainty quantification based on simulated images. Exp Mech 57(6):939–951
Cefalu A, Haala N, Fritsch D (2016) Structureless bundle adjustment with self-calibration using accumulated constraints. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences 3(3):3–9
Dang T, Hoffman C, Stiller C (2009) Continuous stereo self-calibration by camera parameter tracking. IEEE Trans Image Process 18:1536–1550
Hoff W, Ahuja N (1989) Surfaces from stereo: integrating feature matching, disparity estimation, and contour detection, vol 11
Lew MS, Huang TS, Wong K (1994) Learning and feature selection in stereo matching. IEEE Trans Pattern Anal Mach Intell 16:869–881
Matchid, http://www.matchidmbc.com/
Miller TJ, Schreier HW, Reu P (2007) High-speed dic data analysis from a shaking camera system. In: SEM annual conference
Balcaen R, Reu P, Lava P, Debruyne D (2017) Influence of camera rotation on stereo-dic and compensation methods, Submitted to Experimental Mechanics
Stewenius H, Schaffalitzky F, Nister D (2005) How hard is 3-view triangulation really?, IEEE Computer Vision
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Balcaen, R., Reu, P.L. & Debruyne, D. Stereo-DIC Uncertainty Estimation Using the Epipolar Constraint and Optimized Three Camera Triangulation. Exp Tech 42, 115–120 (2018). https://doi.org/10.1007/s40799-017-0207-0
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DOI: https://doi.org/10.1007/s40799-017-0207-0