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arxiv: 2606.28905 · v1 · pith:IZKMQC5Xnew · submitted 2026-06-27 · 💻 cs.CV · cond-mat.mtrl-sci· physics.optics

Projection-based coupling of infrared thermography and stereocorrelation-based digital image correlation

Jendrik-Alexander Tr\"oger , Lutz M\"uller-Lohse , Stefan Hartmann This is my paper

Pith reviewed 2026-06-30 09:51 UTC · model grok-4.3

classification 💻 cs.CV cond-mat.mtrl-sciphysics.optics
keywords infrared thermographydigital image correlationpinhole camera modelradial basis functionsprojection couplingcurved surfacestemperature gradientsfull-field measurements
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The pith

A projection matrix from the pinhole camera model maps two-dimensional infrared temperature measurements onto three-dimensional material points obtained from stereocorrelation digital image correlation.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces a projection-based method to couple infrared thermography data with stereocorrelation-based digital image correlation results. By using the pinhole camera model calibrated on a single reference image, temperature fields are transferred to the 3D coordinates of material points on the specimen surface. This approach works especially well for non-flat, curved surfaces without requiring changes to existing image registration procedures. Radial basis functions are then applied to interpolate the data in space and time, yielding temperature gradients and rates. Researchers in experimental mechanics would value this because it combines deformation and temperature measurements in a common frame for more complete analysis of material behavior.

Core claim

We propose an external projection-based coupling that uses the pinhole camera model to relate two-dimensional temperature data measured by infrared thermography to three-dimensional point coordinates from stereocorrelation-based digital image correlation. The projection matrix of the camera model is calibrated using a single image of a reference object. Through this projection, temperature fields are accurately represented at material points. Additionally, we propose using radial basis functions as a global interpolation ansatz in both space and time to compute in-plane temperature gradients and even temperature rates on curved surfaces, thereby providing an extensive and information-rich fu

What carries the argument

The calibrated projection matrix of the pinhole camera model that maps two-dimensional IR image coordinates to three-dimensional DIC surface points.

If this is right

  • Temperature fields are represented at material points in the Lagrangian frame.
  • The method applies to curved surfaces while leaving existing image registration unchanged.
  • Radial basis function interpolation supplies in-plane temperature gradients and temperature rates.
  • The coupling uses two independent industrial-grade systems and embeds directly into existing experimental protocols.
  • The result is an information-rich full-field dataset combining deformation and thermal quantities.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The single-image calibration may allow routine addition of temperature data to existing stereo DIC setups without new hardware synchronization.
  • Gradient and rate fields from the RBF step could support identification of temperature-dependent constitutive parameters from one test series.
  • On highly curved or deforming surfaces, projection errors might accumulate differently than on the flat calibration object, affecting derived quantities more than raw temperatures.
  • The approach could be tested on dynamic events if the time interpolation in the RBF ansatz maintains accuracy under rapid temperature changes.

Load-bearing premise

The pinhole camera model calibrated with a single image of a reference object sufficiently aligns the independently calibrated infrared and DIC systems without introducing significant errors on non-flat surfaces.

What would settle it

A controlled experiment on a curved specimen with a known temperature distribution where the projected IR values at DIC points deviate measurably from independent contact or calibrated sensor readings beyond stated uncertainty.

Figures

Figures reproduced from arXiv: 2606.28905 by Jendrik-Alexander Tr\"oger, Lutz M\"uller-Lohse, Stefan Hartmann.

Figure 1
Figure 1. Figure 1: Overview of projection and interpolation procedure to couple stereocorrelation-based digital image correlation [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Reference object for camera model calibration. (a) open-book-shaped reference target with point markers, (b) [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Top view of additively manufactured polymer half-shell specimen for thermal analysis on a curved surface [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Temperature field and in-plane temperature gradients on the curved surface of the cylindrical half-shell [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Temperature rate on the curved surface of the cylindrical half-shell [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Experimental setup of the tension-torsion test. a) Alignment of the full-field imaging systems. b) Tube-like [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Tension-torsion test on zinc die-casting alloy. a) Prescribed displacement [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Maximum in-plane principal strain and principal strain directions on the curved surface of the tube-like [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Temperature field and in-plane temperature gradient (scaled by a factor of 8) on the curved surface of the [PITH_FULL_IMAGE:figures/full_fig_p011_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Temperature evolution of a point centered in the curved surface of the tube-like specimen [PITH_FULL_IMAGE:figures/full_fig_p011_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Temperature rate on the curved surface of the tube-like specimen [PITH_FULL_IMAGE:figures/full_fig_p012_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Kinematics of curved surfaces coordinates, a curvilinear surface is parametrized by the surface parameters Ψ = {Ψ1 , Ψ2} ⊤ in both reference configuration R[B] and current configuration χt[B] of the material body B. Note that the reference configuration is assumed to coincide with the initial configuration χt0 [B] at t0. The geometrical vectors X⃗ (Ψ, t0) and ⃗x(Ψ, t) are expressed by means of the surface… view at source ↗
read the original abstract

Full-field measurement techniques such as digital image correlation and infrared thermography are prevalent in experimental solid mechanics. Digital image correlation is used to analyze surface deformation, while infrared thermography quantifies surface temperature fields. However, sophisticated procedures are necessary to express both datasets in the same Lagrangian frame, especially when analyzing non-flat surfaces. In this study, we propose an external projection-based coupling that uses the pinhole camera model to relate two-dimensional temperature data measured by infrared thermography to three-dimensional point coordinates from stereocorrelation-based digital image correlation. Unlike existing multiview approaches, we utilize two independently calibrated industrial-grade systems and augment the experimental evaluation with the pinhole camera model. The projection matrix of the camera model is calibrated using a single image of a reference object. Through this projection, temperature fields are accurately represented at material points. Our method is particularly suited for, but not restricted to, curved surfaces and straightforward to embed in existing experimental protocols, as the image registration is kept as is. Additionally, we propose using radial basis functions as a global interpolation ansatz in both space and time to compute in-plane temperature gradients and even temperature rates on curved surfaces, thereby providing an extensive and information-rich full-field dataset.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The manuscript proposes an external projection-based coupling of infrared thermography and stereocorrelation-based digital image correlation. It uses the pinhole camera model, with the projection matrix calibrated from a single image of a reference object, to map 2D temperature fields onto 3D material points from independently calibrated systems. The approach is presented as suitable for curved surfaces and is augmented by radial basis function interpolation to obtain in-plane temperature gradients and rates.

Significance. If validated, the method would offer a practical route to combine full-field temperature and deformation data on complex geometries while preserving separate industrial-grade calibrations, avoiding the need for integrated multiview setups common in the literature.

major comments (2)
  1. [Abstract] Abstract: the assertion that 'temperature fields are accurately represented at material points' is presented without any validation data, error metrics, reprojection residuals, or experimental comparisons, leaving the central accuracy claim unsubstantiated.
  2. [Abstract] Abstract: the single-image calibration of the 11-DOF projection matrix is claimed to suffice for alignment of independently calibrated IR and stereo-DIC systems on curved surfaces, yet no quantitative bound on mapping error (arising from lens distortion, pose residuals, or planarity of the reference object) is supplied; this directly affects the reliability of the subsequent RBF-derived gradients and rates.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments. We address each major point below and agree that the abstract requires revision to avoid unsubstantiated claims.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the assertion that 'temperature fields are accurately represented at material points' is presented without any validation data, error metrics, reprojection residuals, or experimental comparisons, leaving the central accuracy claim unsubstantiated.

    Authors: The referee correctly notes that the abstract makes this claim without accompanying metrics. The body of the manuscript contains experimental validation and error analysis; however, the abstract itself does not. We will revise the abstract to qualify the statement and reference the specific validation metrics (e.g., reprojection residuals and point-wise temperature mapping errors) reported in the results section. revision: yes

  2. Referee: [Abstract] Abstract: the single-image calibration of the 11-DOF projection matrix is claimed to suffice for alignment of independently calibrated IR and stereo-DIC systems on curved surfaces, yet no quantitative bound on mapping error (arising from lens distortion, pose residuals, or planarity of the reference object) is supplied; this directly affects the reliability of the subsequent RBF-derived gradients and rates.

    Authors: We agree that the abstract should supply a quantitative bound on mapping error to support the claim. The manuscript describes the single-image calibration procedure and its use on curved surfaces, but does not include explicit error bounds in the abstract. We will revise the abstract to include a concise summary of the observed mapping accuracy (including contributions from lens distortion and pose residuals) drawn from the experimental evaluation already present in the paper. revision: yes

Circularity Check

0 steps flagged

No circularity; procedural coupling with independent calibration

full rationale

The paper describes an external projection-based coupling of two independently calibrated systems (IR thermography and stereo-DIC) via a pinhole camera model whose projection matrix is fixed from a single reference image. Temperature fields are then mapped to Lagrangian points and interpolated with radial basis functions. No equations, predictions, or uniqueness claims reduce by construction to fitted inputs, self-definitions, or self-citation chains; the method is a straightforward registration procedure whose validity rests on standard camera calibration assumptions rather than internal re-derivation of its own results.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The approach assumes the validity of the pinhole camera model for relating the two measurement systems and the suitability of radial basis functions for interpolation on curved surfaces. Calibration parameters are data-driven rather than ad hoc free parameters.

free parameters (1)
  • projection matrix parameters
    Calibrated using single image of reference object to relate 2D temperature data to 3D points
axioms (1)
  • domain assumption Pinhole camera model accurately represents the imaging geometry of both independently calibrated industrial-grade systems
    Used to relate 2D temperature data to 3D point coordinates from stereocorrelation-based DIC

pith-pipeline@v0.9.1-grok · 5764 in / 1371 out tokens · 32843 ms · 2026-06-30T09:51:43.716287+00:00 · methodology

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