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Erschienen in: Experimental Mechanics 4/2011

01.04.2011

On Error Assessment in Stereo-based Deformation Measurements

Part I: Theoretical Developments for Quantitative Estimates

verfasst von: Y.-Q. Wang, M. A. Sutton, X.-D. Ke, H. W. Schreier, P. L. Reu, T. J. Miller

Erschienen in: Experimental Mechanics | Ausgabe 4/2011

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Abstract

Using the basic equations for stereo-vision with established procedures for camera calibration, the error propagation equations for determining both bias and variability in a general 3D position are provided. The results use recent theoretical developments that quantified the bias and variance in image plane positions introduced during image plane correspondence identification for a common 3D point (e.g., pattern matching during measurement process) as a basis for preliminary application of the developments for estimation of 3D position bias and variability. Extensive numerical simulations and theoretical analyses have been performed for selected stereo system configurations amenable to closed-form solution. Results clearly demonstrate that the general formulae provide a robust framework for quantifying the effect of various stereo-vision parameters and image-plane matching procedures on both the bias and variance in an estimated 3D object position.

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Fußnoten
1
When x is n-dimensional, the covariance matrix (also called the variance-covariance matrix) is usually denoted Var(x) and has the expression:
$$ Var({\mathbf{x}}) = E(({\mathbf{x}} - E({\mathbf{x}})){({\mathbf{x}} - E({\mathbf{x}}))^T}) = \left[ {\begin{array}{*{20}{c}} {{\sigma_{{x_1}}}^2} & {{\rm cov} ({x_1},{x_2})} & . & . & {{\rm cov} ({x_1},{x_n})} \\{{\rm cov} ({x_2},{x_1})} & {{\sigma_{{x_2}}}^2} & . & . & . \\. & . & . & . & . \\. & . & . & . & . \\{{\rm cov} ({x_n},{x_1})} & . & . & . & {{\sigma_{{x_n}}}^2} \\\end{array} } \right] $$
 
2
The cost function is usually obtained from bundle adjustment or other similar optimization methods.
 
3
Equation (10) in reference [8] is incorrect; the IM should be IN
 
4
It is assumed that all images have been corrected for distortions. Non-parametric methods [14] provide one approach that can be used to remove distortions so that the pinhole mode
 
5
The initial world system orientation relative to the camera 1 system is commonly used as the reference for all 3D measurements. For this reason, it is separated from the remaining Nviews extrinsic parameter variables.
 
6
During calibration, it is common to arrange the initial world system to coincide with the planar grid/dot pattern configuration and thereby simplify the analysis.
 
7
It is assumed that the radial distortion model provides an exact representation for the deviations relative to the pinhole model.
 
8
Figure 1 assumes ideal pinhole model projection to simplify the presentation.
 
9
The large subset size was selected to be consistent with use of previously published experimental data [13]. The large subset size was used to obtain sufficient pattern density and local contrast for accurate matching, since the pattern was quite coarse at the high magnification employed by the authors to achieve pixel translations in increments of ≈ 0.07 pixels.
 
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Metadaten
Titel
On Error Assessment in Stereo-based Deformation Measurements
Part I: Theoretical Developments for Quantitative Estimates
verfasst von
Y.-Q. Wang
M. A. Sutton
X.-D. Ke
H. W. Schreier
P. L. Reu
T. J. Miller
Publikationsdatum
01.04.2011
Verlag
Springer US
Erschienen in
Experimental Mechanics / Ausgabe 4/2011
Print ISSN: 0014-4851
Elektronische ISSN: 1741-2765
DOI
https://doi.org/10.1007/s11340-010-9449-9

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