# Virtual Reality in Cultural Heritage: A Setup for Balzi
## 3 Materials and Methods
### Second Iteration of the Balzi Rossi VR Experience
The intensity at which snow is applied beyond a certain degree of inclination is controlled using the Lerp node, which performs a linear interpolation between two known values (A and B) with an alpha constant ranging from 0 to 1. To recreate a winter environment (Figure 7) with ongoing snowfall, the Exponential Height Fog and Sky Atmosphere components were properly configured. The former creates  
Figure 6: Comparison of Balzi Rossi cliff between a drone orthophoto (**left**), the first virtual reconstruction (**center**), and the second virtual reconstruction (**right**). a fog system with higher density in lower altitude areas and vice versa, managing two colors: one for the hemisphere facing the main directional light and one for the opposite side. The Sky Atmosphere component simulates light dispersion through the atmosphere, considering factors like sky color and directional light, and includes Mie scattering and Rayleigh scattering effects for dynamic sky simulation [23]. For the snowflakes, a Niagara system with modified textures was created to simulate real snow instead of simple white circles. This particle system was attached to the VR pawn, so the emitter created particles locally, maintaining good performance and graphic rendering. The same optimizations applied to the foliage in the main level were used for the forest, but with fewer elements, allowing the retention of dynamic shadows. The movement system has been enhanced and modified in the latest version. Initially, the basic system provided by Unreal was used, allowing movement through teleportation to minimize motion sickness. However, in the current iteration, this system has been completely redeveloped to incorporate smooth and continuous movement using analog sticks, offering users greater freedom for movement and exploration, despite the potential increase in motion sickness. This was accomplished by converting the VR player pawn into a player character, ensuring a more robust structure that prevents passing through objects. The movement programming has been updated to incorporate continuous motion. Additionally, a tutorial has been introduced to guide users on how to employ both methods of movement, a feature that was absent in the previous version. Lastly, for debugging tools to assess performance during landscape construction and DLSS adoption, Unreal Insights was used. This tool provides highly detailed, frame-by-frame data on draw calls, CPU, GPU, and resources used by each scene element. Another essential VR debugging tool was Oculus Debug Tools, providing an overlay in the head-mounted display (HMD) containing basic in-game performance information. This tool was used to monitor FPS and hardware usage in the executable of the experience, where Unreal tools are challenging to use. Another major improvement over the first version was making the experience multi-language, making tutorials and infographics available in Italian, English, and French. We have opted for Italian and French as the primary languages of the project, given the archaeological site's unique position near the border between Italy and France. English has been adopted as the lingua franca to facilitate broader international engagement. Additionally, in our team, we have experts who are fluent speakers of these languages who have been able to validate the translations.