## 4 Experiments and Results
### The Roman Villa of Aiano  
The Roman villa of Aiano is an Italian archaeological site in Tuscany, close to San Gimignano and its remains date back between the end of the 3 rd and the 7 th century A.D. Since 2005 the villa has been excavated by an Italian-Belgian mission coordinated by the UCLouvain as part of the international project \"VII Regio. The Elsa Valley during Roman Age and Late Antiquity\" [82]. During the research, a 3D model of the so-called trefoil hall was performed in collaboration with the ISPEC-CNR in order to simulate a possible reconstruction of the archaeological remains, characterised by monumental architecture and decorations, and, above all, to better understand the architectural evolution phases of the hall. Three different model have been produced: (1) a digital replica model of the site in its current state of preservation, obtained with image-based modelling techniques; (2) a schematic semantic model which allows to query information and sources used in the reconstructive process and visualise level of certainty using different colour coding to distinguish extant structures from virtual reconstruction; (3) a realistic virtual reconstruction which simulates the building in its formal unity and in its hypothetical aspect at the end of the 4 th century A.D., to improve legibility of the hall [83]. The digital replica model was exported in glTF format in order to assess vocal annotations offered by [PERSON] (see Section 3.8) by means of semantic shapes on an ATON scene. Different vocal notes have been recorded and associated with semantic shapes, placed on specific points of interest like architectural decorations or structures. Figure 20 shows  
Figure 19: A different setup to assess multiple light-probes on 3 instances of the 3D model. an example of this workflow: the Western apse of the hall shows an _opus signinum_ floor decoration in which the _tesserae_ form the image of a vase (_Kantaras_). Using the free-form shape annotation tool, the area of the apse was drawn. Then, a vocal note, in which the peculiarities of the floor decoration are highlighted, has been recorded using the built-in PC microphone. Results  
The identified area for the experiment was segmented in 16 blocks for the reality based layer (modern), in addition to the reconstruction layer (semi-transparent volumes) on top (see Figure 20, bottom left). The blocks (obj format) and referenced textures were converted to the gITF format with Draco compression for geometries, populating the cloud collection in order to assemble the scene. As shown in Table 2 Draco compression provided by Cesium tools ([[https://github.com/CesiumGS/glft-pipeline](https://github.com/CesiumGS/glft-pipeline)]([https://github.com/CesiumGS/glft-pipeline](https://github.com/CesiumGS/glft-pipeline)), accessed on 22 November 2021) was particularly effective on original obj size (106 Mb compressed in 2.43 Mb) using compression level = 4. After the creation and publication of the 3D scene on the server, the entire annotation workflow was carried out autonomously by an authenticated researcher directly through Hathor front-end, using a web browser. First, scene cloning (see Section 3.2) allowed the researcher to duplicate the original 3D scene (available at [[https://aton.ispc.cnr.it/s/vhlab/demo/aiano](https://aton.ispc.cnr.it/s/vhlab/demo/aiano)]([https://aton.ispc.cnr.it/s/vhlab/demo/aiano](https://aton.ispc.cnr.it/s/vhlab/demo/aiano)), accessed on 22 November 2021) for the experiment, thus reusing the same assets in a different scene (with a different scene ID). On the new scene, the time spent to annotate 5 different areas using the free-form annotation tool (see Figure 20) was around 6 min, using mouse and keyboard on a desktop PC equipped with a NVIDIA GTX 980 GPU. Once edited, the 3D scene including voice annotations was accessed using different devices (PC, mobile smartphone and tablet, HMD) recording average fps for 4 min. In order to assess cross-device presentation features, the same 3D scene was accessed and