The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-2/W4-2024
https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-73-2024
https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-73-2024
14 Feb 2024
 | 14 Feb 2024

OPTIMIZATION OF VR APPLICATION IN TEXTURING CULTURAL HERITAGE

C. M. Bolognesi and V. Manfredi

Keywords: VR, Level of Immersivity, Remeshing, Texturing, CPU-GPU

Abstract. The research question underlying this short essay refers to the possibility of realizing through a well-established workflow a high level of immersivity in the VR representation of Cultural Heritage to be used as a working tool by architects and renovators as well as heritage scholars. At present active or passive 3D scanning techniques are a known reality where the choice of data acquisition system depends both on the final purpose and characteristics of the object to be surveyed. With the maturity achieved in point cloud acquisition, post processing phases and the development of BIM-based systems, the model has given the possibility to become a repository of information related to the existing, to be used for maintenance or renovation processes. If the model can represent the existing with a certain level of detail, it can be assumed that a differentiated Level of Immersivity can be organized depending on the specific needs it intends to fulfil. In the context of renovation or preservation of Cultural Heritage, the potential offered by VR becomes more interesting when it can provide a realistic portrait not only of the geometry, but also of the materiality and state of preservation of the buildings. This research opens new possibilities to develop tools to aid designers and renovators in degradation analysis, intervention projects, and scheduled maintenance. The research question starts analyzing the possibility of creating photorealistic immersive environments that are easy to access, organized based on surveys of existing heritage buildings using specific datasets.