## 3 Virtual Reconstruction Workflow for Sculptal Fragments
### Primary Data Sources' Acquisition: 3D Survey and Reality-Based Model Creation  
The 3D survey can be performed using both range-based and image-based techniques; the choice depends on various conditions such as the size of the object, the location, etc. Range-based techniques are generally the most reliable for large sculptural groups, but, in most cases, they show limitations in reproducing the chromatic features, unlike image-based techniques, which are able to capture realistic textures and high detailed models starting from a series of high-resolution images. For this reason, in order to achieve the best results from 3D survey techniques, range-based and image-based techniques are often integrated. Prior to starting the survey, a few elements were considered: the state of conservation of the statues, their sizes and type of material, their position in the museum hall, and the lighting conditions. The most critical aspect of the survey was the position of the statues, which were very close to the wall. In order to prevent any problem, the 3D survey was conducted with both range-based and image-based techniques. A range-based survey was carried out first using the Stonex F6 3D handheld laser scanner; this device allows the acquisition of 3D models of medium-large objects in dynamic motion. The survey was carried out with an average distance between the instrument and the statues of about 50-60 cm. The execution was supported via tablet by real-time data visualization (Figure 6). The laser scanning survey allowed the acquisition of point clouds of the entire statues with an average resolution of a few millimetres. After the acquisition, 3D scans of _[PERSON]_ and _[PERSON]_ statues were processed with the Stonex-Echo software that produced very detailed 3D meshes. A close-range photogrammetric survey was carried out using a Nikon D5200 digital camera, equipped with 24-55 mm lenses and a maximum resolution of 6000 \(\times\) 4000 pixels. Image acquisition was carried out with a 24 mm focal length by executing a very close-range convergent acquisition. For the statue of _[PERSON]_, a total of 55 images were required; for _[PERSON]_, a total of 48 images were needed. Smaller fragments--one female and one  
Figure 5: Virtual sculptural reconstruction workflow. male shot foot--were also acquired. In Table 1, details of the photogrammetric survey are reported. Images were processed with the Agisoft-Metashape package. Image alignment was the first step; then a dense point cloud and a textured mesh were generated (Figure 7). Some distances were measured on the laser scanner models in order to scale the photogrammetric models. The same photogrammetric process was carried out for smaller fragments but the scaling procedure was performed by applying one or more scalebars into the scene during the survey. The models generated for both status using photogrammetric techniques were conducted to the same reference system of the laser scanner 3D model, by a cloud-to-cloud registration using CloudCompare and the \"Fine registration\" tool. This tool can automatically finely register two different point clouds or meshes using a modified ICP (Iterative Closest Point) algorithm able to also determine a potential difference in scaling between the two datasets. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Special Finds** & **N. of Images** & **Focal Length** \\ \hline _Aesculapius_ statue & 55 & 24 mm \\ _Hryecia_ statue & 48 & 24 mm \\ _Aesculapius_ right foot & 24 & 40 mm \\ _Hryecia_ left foot & 34 & 55 mm \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Details of the photogrammetric survey of the Special Finds. Figure 6: 3D laser scanner survey of the _Aesculapius_ and _Hryecia_ status: (**a**) Stonex F6 acquisition; (**b**) real-time visualization. Figure 7: Agisoft-Metashape photo alignment step of the _Aesculapius_ (**a**) and _Hryecia_ status (**b**). Two 3D models from the handheld laser scanner and photogrammetry for both status were thus obtained (Figure 8).