## 4 Conclusions
### Future Works  
This project work achieved a fluid visualization experience at 60+ FPS with highly physical dimensions models such as the entire \"Parco di Monza\", in order to accomplish obtaining the most complete experience, a combination of both highly detailed models at architectural scale and lowly detailed models at urban scale has been employed, thereby achieving the highest level of detail possible for Point Of Interests (POI) while utilizing environment contexts for the spatial location and green areas. Future studies on the application comprise four possible areas:  
The first area for future studies is related to content creation. The application at its current state allows for easy widget insertion inside the models via the Unity interface, user experience can be improved with new scenarios correlating the past and the present of POIs, and the beforementioned Google Maps toolchain allows for easily retrievable 3D models of high-scale dimensions with little to no cost and effort. Furthermore, for a more personalized experience around the personas involved, it is possible to create new widgets with custom behaviors, linking them to the present interface optimized for the most scalable solution with new widgets. Another future study area that can be employed involves performance optimization. The proposed toolchain succeeds in obtaining low-size models from Google Maps, but both low- and high-detail models can be improved for performance by size-reduction techniques, which include, but are not limited to, retopology for a cleaner and lighter representation while matching the same physical shape, texture optimization, normal maps, and so on. Other performance-related improvement involves utilizing LOD logic for better optimization of the process of allocating computational power to render the focused building, silently reducing the level of detail of surroundings and border objects. Another interesting future study area may involve personalization over the application. Different personas may be interested in different points of view and POIs, for which a recommender system [32] may be employed for further personalization according to the user's taste and interest [33]. Lastly, the Quality Of Experience (QoE) of the user depends on multiple factors. Although latency-related causes were addressed in the \"Results\" section, it is worth noticing that the quality of the image plays a key role in the user comfort analysis. The holographic table device and 3D rendering of the 2D screens may introduce image distortions that could lead to user discomfort, loss of visual data, and an overall worse quality of experience. It goes without saying that this factor needs to be analytically measured and evaluatedin importance related to the specific experience; these metrics require comprehending distortion factor introduction, analysis, and methodologies to overcome their negative effects, such as Blind Multiple Pseudo Reference Image (BMPRI)-based measure and the Blind Pseudo Reference Image (BPRI) [34; 35]. Image quality assessment is a challenging task for this kind of application, as the visual representation of the environment is often subject to distortions due to hardware capabilities (AR tracking glasses, holographic table infrared tracker cameras, etc.) or user-dependent causes (depth perception, eyes related problems, etc. ); assessing the quality of the image may be conducted with techniques such as Blind Pseudo Reference Image and Blind Multiple Pseudo Referenced Image. MPRI is a general-purpose Blind Image Quality Assessment (BIQA) method for distortion estimation. The blind characteristics make it Opinion Unaware (OU), and is thus suitable for applications with a high volume of information subject to variable distortion. On the other hand, BMPRI is a metric for measuring the QoE of the user employing images subjected to distortion, and it is obtained via the extension of pseudo-referenced images (PRI) to the beforementioned Multiple Pseudo Referenced Image (MPRI). Conceptualization, C.M.B., D.B. and D.S.