It is proposed to develop a multiview framework to perform stereocorrelation by resorting to isogeometric descriptions of the observed three-dimensional surfaces. Once the three-dimensional surfaces have been reconstructed, the corresponding three-dimensional displacement fields are measured within the same space. These fields are subsequently utilized to update isogeometric analyses to calibrate the elastic properties in a tensile experiment. An alternative route consists of preforming such analyses within an integrated framework.
SuttonMA. Computer vision-based, noncontacting deformation measurements in mechanics: a generational transformation. Appl Mech Rev2013; 65: 050802.
2.
BroggiatoGB. Adaptive image correlation technique for full-field strain measurement. In: Proceedings of the 12th international conference on experimental mechanics (ed PappalettereC), Bari, 29 August 2004, pp.420–421. Milan: McGraw-Hill.
3.
SunYPangJWongC. Finite-element formulation for a digital image correlation method. Appl Optics2005; 44(34): 7357–7363.
4.
BesnardGHildFRouxS. “Finite-element” displacement fields analysis from digital images: application to Portevin-Le Châtelier bands. Exp Mech2006; 46: 789–803.
5.
HildFRouxS. Digital image correlation. In: RastogiPKHackE. (eds) Optical Methods for Solid Mechanics: A Full-Field Approach. Weinheim: Wiley-VCH, 2012, pp.183–228.
6.
CottrellJAHughesTJRBazilevsY. Isogeometric analysis: toward integration of CAD and FEA. Chichester, UK: Wiley, 2009 .
7.
BeaubierBDufourJEHildF. CAD-based calibration of a 3D-DIC system: principle and application on test and industrial parts. Exp Mech2014; 54(3): 329–341.
8.
DufourJEBeaubierBRouxS. Displacement measurement using CAD-based stereo-correlation with meshes. In: Proceedings of the ICEM conference, University of Cambridge, 7–11 July 2014.
9.
SuttonMAHildF. Recent advances and perspectives in digital image correlation. Exp Mech2015; 55(1): 1–8.
10.
KavanaghKT. Extension of classical experimental techniques for characterizing composite-material behavior. Exp Mech1972; 12(1): 50–56.
11.
KavanaghKTCloughRW. Finite element applications in the characterization of elastic solids. Int J Solids Struct1971; 7: 11–23.
12.
CollinsJDHartGCHasselmanTK. Statistical identification of structures. AIAA J1974; 12(2): 185–190.
13.
AvrilSBonnetMBretelleAS. Overview of identification methods of mechanical parameters based on full-field measurements. Exp Mech2008; 48(4): 381–402.
14.
GrédiacMHildF (eds). Full-field measurements and identification in solid mechanics. London: ISTE/Wiley, 2012.
15.
HildFRouxS. Digital image correlation: from measurement to identification of elastic properties—a review. Strain2006; 42: 69–80.
16.
RouxSHildF. Stress intensity factor measurements from digital image correlation: post-processing and integrated approaches. Int J Fract2006; 140(1–4): 141–157.
17.
LeclercHPériéJNRouxS. Integrated digital image correlation for the identification of mechanical properties, vol. LNCS 5496. Berlin: Springer, 2009, pp.161–171.
18.
RéthoréJ. A fully integrated noise robust strategy for the identification of constitutive laws from digital images. Int J Num Meth Eng2010; 84(6): 631–660.
19.
MathieuFLeclercHHildF. Estimation of elastoplastic parameters via weighted FEMU and integrated-DIC. Exp Mech2015; 55(1): 105–119.
20.
PieglLTillerW. The NURBS book. 2nd ed.New York, NY, Springer, 1997.
21.
DufourJ-EBeaubierBHildF. Shape measurement using CAD-based stereo-DIC. In: JinHSciammarellaCYoshidaS (eds) Advancement of optical methods in experimental mechanics: conference proceedings of the Society for Experimental Mechanics series, vol. 3. Springer, 2014, pp.333–338, DOI: 10.1007/978-3-319-00768-7_43.
22.
DufourJ-EBeaubierBHildF. CAD-based displacement measurements with stereo-DIC. Principle and first validations. Exp Mech2015, DOI:10.1007/s11340-015-0065-6.
23.
FaugerasO. Three-dimensional computer vision: a geometric viewpoint. Cambridge, MA: MIT Press, 1993.
24.
SuttonMAOrteuJJSchreierH. Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. New York: Springer, 2009.
25.
FaugerasODLuongQTMaybankSJ. Camera self-calibration: theory and experiments. In: Proceedings of the 2nd ECCV, Santa Margherita Ligure, 19–22 May 1992, pp.321–334. Berlin, Heidelberg: Springer-Verlag.
26.
De FalcoCRealiAVázquezR. GeoPDEs: a research tool for isogeometric analysis of PDEs. Adv Eng Softw2011; 42(12): 1020–1034.
27.
GrasRLeclercHHildF. Identification of a set of macroscopic elastic parameters in a 3D woven composite: uncertainty analysis and regularization. Int J Solids Struct2015; 55: 2–16.
28.
HildFRouxS. Comparison of local and global approaches to digital image correlation. Exp Mech2012; 52(9): 1503–1519.
29.
CoonsS. Surface patches and B-spline curves. In: BarnhillRERiesenfeldRF (eds) Computer aided geometric design. New York: Academic Press, 1974, pp.1–16.
30.
RouxSHildF. Digital image mechanical identification (DIMI). Exp Mech2008; 48(4): 495–508.
31.
GarciaDOrteuJJRobertL. A generic synthetic image generator package for the evaluation of 3D digital image correlation and other computer vision-based measurement techniques. In: Proceedings of Photomechanics2013, http://hal.archives-ouvertes.fr/hal-00836324
32.
BeslPJMcKayND. A method for registration of 3-D shapes. IEEE T Pattern Anal1992; 14(2): 239–256.
33.
ChenYMedioniG. Object modelling by registration of multiple range images. Image Vision Comput1992; 10(3): 145–155.
34.
ZhangZ. Iterative point matching for registration of free-form curves and surfaces. Int J Comput Vision1994; 13(2): 119–152.
35.
HarventJCoudrinBBrèthesL. Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system. Mach Vision Appl2013; 24(8): 1645–1659.
