Reconstructing accurate 3D models of archaeological artifacts, particularly painted ones like frescoes, presents significant challenges due to their complex geometries and the need to capture detailed pictorial information. Traditional 3D scanning technologies excel in geometry but fall short in capturing texture quality, making RGB cameras a better choice for painted artifacts. This paper proposes a comprehensive pipeline that integrates automated segmentation with photogrammetric tools to address these issues. The semi-automatic segmentation phase minimizes manual effort while ensuring accurate mask generation for intricate artifacts, and the reconstruction process efficiently produces dense 3D models with high geometric and textural fidelity. The final registration of models ensures precise alignment, resulting in an accurate and detailed reconstruction. Tested on fragmented frescoes as part of the EU Horizon 2020 RePAIR project, our pipeline demonstrates a scalable and computationally efficient solution for large-scale CH digitization and restoration, aiding the reassembly of fragmented artifacts with minimal manual input.

Automatizing 3D reconstruction pipelines for speeding-up cultural heritage digitization / G. Bison, L. Palmieri, S. Aslan, S. Vascon, M. Pelillo. - In: MULTIMEDIA TOOLS AND APPLICATIONS. - ISSN 1573-7721. - (2025), pp. 1-21. [Epub ahead of print] [10.1007/s11042-025-20918-8]

Automatizing 3D reconstruction pipelines for speeding-up cultural heritage digitization

S. Aslan;
2025

Abstract

Reconstructing accurate 3D models of archaeological artifacts, particularly painted ones like frescoes, presents significant challenges due to their complex geometries and the need to capture detailed pictorial information. Traditional 3D scanning technologies excel in geometry but fall short in capturing texture quality, making RGB cameras a better choice for painted artifacts. This paper proposes a comprehensive pipeline that integrates automated segmentation with photogrammetric tools to address these issues. The semi-automatic segmentation phase minimizes manual effort while ensuring accurate mask generation for intricate artifacts, and the reconstruction process efficiently produces dense 3D models with high geometric and textural fidelity. The final registration of models ensures precise alignment, resulting in an accurate and detailed reconstruction. Tested on fragmented frescoes as part of the EU Horizon 2020 RePAIR project, our pipeline demonstrates a scalable and computationally efficient solution for large-scale CH digitization and restoration, aiding the reassembly of fragmented artifacts with minimal manual input.
3D Reconstruction; Automated generation of segmentation masks; Cultural heritage digitization
Settore INFO-01/A - Informatica
2025
18-giu-2025
https://link.springer.com/article/10.1007/s11042-025-20918-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1175864
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