Abstract
In an augmented reality project dealing with complex objects with a large scale, it is necessary to minimize the number of polygons of a mesh. The challenge is trying to find a compromise between accuracy, details and fluidity of the representation. Starting from two different surveys (Laser Scanner and Photogrammetry) with high resolution, two paths have been identified: the first one consists on the retopology of the mesh obtained from the point cloud with the help of software like Instant Mesh; the second one relies on the complete re-modelling of the artefact, trying to simplify its structure in macro-elements using Retopoflow tool in Blender. The level of detail is preserved in both cases: in the first, the “quad mesh” keeps complex geometries minimizing the number of polygons; in the other an accurate management of texture of PBR materials returns realism with simple shapes, with a lower number of polygons. These methods have been applied to the reconstruction of San Lorenzo Bridge, one of the ancient monuments of the Roman Padova no longer visible, examined by the research project PD-Invisible. Results validate that the second method is more effective, ensuring an excellent realism in the rendering phases, minimizing the size of the file.
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Acknowledgements
The activity presented in the paper is part of the research grant “FSE 2105-18-11-2018, PD-Invisible: PaDova INnovative VISions – visualizations and Imaginings Behind the city Learning”. We would like to express our appreciation to Comune di Padova, Musei Civici agli Eremitani and Soprintendenza Archeologia, Belle Arti e Paesaggio per l’area metropolitana di Venezia e le province di Βelluno, Padova e Treviso for the endorsement and the collaboration.
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Perticarini, M., Callegaro, C., Carraro, F., Mazzariol, A. (2020). Two Methods of Optimization for an AR Project: Mesh Retopology and Use of PBR Materials. In: Cicalò, E. (eds) Proceedings of the 2nd International and Interdisciplinary Conference on Image and Imagination. IMG 2019. Advances in Intelligent Systems and Computing, vol 1140. Springer, Cham. https://doi.org/10.1007/978-3-030-41018-6_82
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DOI: https://doi.org/10.1007/978-3-030-41018-6_82
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