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F. Franceschini

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Open access Sep 2026

Enhancing the quality of object inspections by combining photogrammetry and Gaussian Splatting

Inspection activities on industrial assets, for instance in the aerospace or automotive industry, frequently pertain to the examination of the surface conditions of objects. Among the established techniques for surface assessment, photogrammetry has gained increasing relevance in manufacturing quality monitoring, due to its ability to provide high-fidelity 3D spatial data. However, during the photogrammetric reconstruction of a physical object, some regions may be reconstructed less accurately, for example due to an insufficient number of local photographic acquisitions; in such cases, additional photographs of these regions would be needed. This, however, requires the object to remain accessible and unchanged from the time of the initial acquisition; in practice, this condition is rarely met, as the object is often no longer accessible or is found in a different state. Therefore, photogrammetry is intrinsically tied to the acquisition moment, since it relies on images captured at a specific time and does not allow purpose-driven further inspection. This paper proposes a solution to this limitation of traditional photogrammetry, exploiting the concept of “3D scene”, defined as a high-fidelity digital representation of an object at a specific moment in time. Recent advances in radiance-field methods, particularly Gaussian Splatting (GS), enable the creation of fully navigable 3D frozen-in-time scenes, allowing for the extraction of digital images, i.e., renders, that can be integrated into the photogrammetric process to enhance reconstruction quality. The most significant advantage of GS-based scenes is that they are generated from exactly the same photographs used for the preliminary (and sometimes incomplete) photogrammetric reconstruction, without requiring any additional acquisitions. This combined use of photogrammetry and GS introduces the innovative paradigm of back-in-time inspection into manufacturing. This study addresses two main research questions: (i) How can the combined use of photogrammetry and GS be employed for inspection tasks? and (ii) To what extent does GS improve reconstruction completeness and defect detectability? A case study in the aerospace sector is proposed to demonstrate the effectiveness of this method.

M. Trombini, D. Maisano, F. Franceschini · 0 citations
Review Open access Aug 2026

Photogrammetry and gaussian splatting to improve surface inspections

Physical inspections in various contexts (industrial, operational, medical, etc.) often require surface analysis, but how is it possible to review or improve past inspections retrospectively, even when the object under investigation is no longer available? Classical photogrammetry enables 3D reconstructions but often struggles with incomplete photo sets or noise. This study integrates photogrammetry with Gaussian Splatting, a recent technique enhancing visualisation via colour-based 3D rendering; virtual images obtained from Gaussian-Splatting renders enable the retrospective revisiting of photogrammetry-based reconstructions, improving their quality and accuracy. Two case studies in aerospace maintenance and medical imaging suggest that this approach can enhance ex-post surface inspections, allowing for a closer examination of details that were initially overlooked. The novelty of this contribution lies in the use of virtual renderings not only for visualisation purposes, but also as supplementary data to enrich 3D reconstruction, combining the visual strength of Gaussian Splatting with the geometric reliability of photogrammetry.

M. Trombini, D. Maisano, F. Franceschini · 0 citations

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