## 3 Results
### Latency Sensibility Analysis
#### 3.2.3 Analysis Mesh-Latency
The results (Figure 9) reveal that 81% of the model mesh has an adherence within a 0.66 m range from the point cloud model, and 94.9% of the model mesh has an adherence within a 1.31 m range from the point cloud. This indicates that the low-accuracy models maintain a reasonably high level of adherence to the high-accuracy models, despite their lower level of details. These findings suggest that low-accuracy models obtained using the FOSS toolchain are capable of providing a minimum quality level that is suitable for the AR application on a holographic table. While they may not capture all the fine details of the high-fidelity models, they still provide a visually accurate representation of the model with a high level of adherence to the original point cloud data (Figure 10). This supports the feasibility of using low-accuracy models to optimize the application's performance by reducing the file size and computational costs, while still maintaining an acceptable level of quality for user experience. Figure 9: Adherence of the best accuracy mesh to the low-accuracy model. In the right image blue indicates a difference between the two meshes with an indentation of the second mesh on the first; red a difference detected as a protrusion of the second mesh on the first; green the two meshes coincide. To assess the performance of the application, a series of experiments were conducted using the Unity Analysis Profiler. Since rendering was a crucial task in the application, the main performance metric analyzed was the FPS amount during the rendering phase, which is critical for performance-related motion sickness. Five separate experiments with both low-detailed and highly detailed models employed were conducted with different setups to determine the most significant ones for the results presented in this paper. The experiments included the following (Figure 11):  
1. Loading the most highly detailed survey model, \"Torretta Viscontea\", directly into the application with an approximate file size of 1.81 GB. 2. Loading the less highly detailed survey model, \"Torretta Viscontea\", directly into the application, with an approximate file size of 0.73 GB. 3. Loading only the low-resolution environment of \"Parco di Monza\", with a tiny file size of only 14 MB. 4. Loading the low-resolution environment of \"Parco di Monza\" and the lowest high-fidelity survey of \"Torretta Viscontea\". 5. Loading the low-resolution environment of \"Parco di Monza\" and subsequently both high-fidelity surveys of \"Torretta Viscontea\". The results of the experiments, including the maximum, minimum, and average frame rates, as well as the total frames processed within a 30 s time span, are shown in Table 2. Since the application is closely related to video games, the Frame Per Seconds (FPS) requirement can be safely applied as a metric for this analysis [30]. The minimum FPS for an overall enjoyable experience is typically considered to be 30 FPS, although more experienced users in mixed reality and gaming applications may require a minimum of 60 FPS [31]. The FPS for each experiment during the 30 s time span is shown in the following figures. It is important to note that a maximum buffer of 2000 frames was maintained with the Unity Analysis Profiler, resulting in 2000 frames processed if the minimum FPS requirement was met. This allowed for a comprehensive analysis of the application's performance during the experiments. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Latency MIN [ms]** & **Latency MAX [ms]** & **Latency AVG [ms]** & **Tot. Frames** \\ \hline High Quality & 31.38 & 144 & 87.69 & 170 \\ Low Quality & 3 & 18.61 & 10.81 & 2000 \\ Parco & 4.8 & 7.38 & 6.09 & 2000 \\ Parco + Low & 6.58 & 28.06 & 17.32 & 1754 \\ Parco + Low + High & 10.42 & 189 & 99.71 & 158 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental results of the application latency over various models. Figure 10: A direct comparison between Google Maps mesh and point cloud adherence over the resulting highly accurate mesh of “Torretta Viscontea”.