Scan4Reco: Multimodal Scanning of Cultural Heritage Assets for their multilayered digitization and preventive conservation via spatiotemporal 4D Reconstruction and 3D Printing

Funded by: EU H2020Reference: H2020-REFLECTIVE-7-2014 665091
Start: 2015-10-01Duration: 36 months
Coordinator: CERTHGreece
Contractor: IDRYMA ORMYLIAGreece
Contractor: Fraunhofer IGDGermany
Contractor: University of VeronaItaly
Contractor: Opificio delle Pietre DureItaly
Contractor: CRS4Italy
Contractor: BWTek Europe GmbHGermany
Contractor: Avasha AGSwitzerland
Contractor: RFSATUK


Scan4Reco will develop a novel portable, integrated and modular solution for customized and thus cost-effective, automatic digitization and analysis of cultural heritage objects (CHOs), even in situ. A multi-sensorial 3D scanning - facilitated by a mechanical arm – will collect multi-spectra data and then, a hierarchical approach for 3D reconstruction of CHOs will be applied, enabling multi-layered rendering, advancing both analysis and 3D printing procedures. The goal will be to create highly accurate digital surrogates of CHOs, providing also detailed insight over their surface and also the volumetric structure, material composition and shape/structure of underlying materials, enabling rendering either via visualization techniques or via multi-material 3D printing. Material analyses will be applied, to understand the heterogeneous nature and complex structures of CHOs, to identify the broad and varied classes of materials and to understand their degradation mechanisms over time, deriving context-dependant ageing models per material. Uni-material models will be spatiotemporally simulated, based on environmental phenomena modeling, so as to collectively render imminent degradation effects on the multi-material CHOs, enabling prediction and recreation of their future appearance, as well as automatic restoration, reaching even back to their original shape. Scan4Reco will further facilitate conservation, by indicating spots/segments of cultural objects that are in eminent conservation need and require special care, while suggestions will be provided by a dedicated Decision Support System (DSS), over conservation methods that should be followed. All the above will be validated on real case scenarios involving heterogeneous objects of various sizes and materials, in 2 pilot real-world use cases. To enhance the accessibility of the digitized cultural objects to the scientific community, field experts and the general public, a virtual model of a museum will be launched.


[1] Andrea Giachetti, Irina Ciortan, Claudia Daffara, Ruggero Pintus, and Enrico Gobbetti. Multispectral RTI Analysis of Heterogeneous Artworks. In The 14th Eurographics Worhshop on Graphics and Cultural Heritage, October 2017. To appear. 
[2] Ruggero Pintus, Andrea Giachetti, and Enrico Gobbetti. Guided Robust Matte-Model Fitting for Accelerating Multi-light Reflectance Processing Techniques. In Proc. British Machine Vision Conference, September 2017. To appear. 
[3] Andrea Giachetti, Irina Ciortan, Claudia Daffara, Giacomo Marchioro, Ruggero Pintus, and Enrico Gobbetti. A Novel Framework for Highlight Reflectance Transformation Imaging. Computer Vision and Image Understanding, 2017. To appear. 
[4] Ruggero Pintus, Ying Yang, Holly Rushmeier, and Enrico Gobbetti. Automatic Algorithms for Medieval Manuscript Analysis. In Proc. 18th International Graphonomics Society Conference, June 2017. To appear. 
[5] Marco Agus, Enrico Gobbetti, Fabio Marton, Giovanni Pintore, and Pere-Pau Vázquez. Mobile Graphics. In Adrien Bousseau and Diego Gutierrez, editors, Proc. EUROGRAPHICS Tutorials, April 2017.
[6] Ruggero Pintus, Enrico Gobbetti, Marco Callieri, and Matteo Dellepiane. Techniques for seamless color registration and mapping on dense 3D models. Pages 355-376, Springer, 2017.
[7] Ruggero Pintus, Irina Ciortan, Andrea Giachetti, and Enrico Gobbetti. Practical Free-form RTI Acquisition with Local Spot Lights. In Proc. Smart Tools and Apps for Graphics (STAG), October 2016.
[8] Irina Ciortan, Ruggero Pintus, Giacomo Marchioro, Claudia Daffara, Andrea Giachetti, and Enrico Gobbetti. A Practical Reflectance Transformation Imaging Pipeline for Surface Characterization in Cultural Heritage. In The 13th Eurographics Worhshop on Graphics and Cultural Heritage, October 2016.