Browsing by Author "Antonini, Marc"

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    Graph-based Computation of Voronoi Diagrams on Large-scale Point-based Surfaces
    (The Eurographics Association, 2022) Bletterer, Arnaud; Payan, Frédéric; Antonini, Marc; Pelechano, Nuria; Vanderhaeghe, David
    We present an original algorithm to construct Voronoi tessellations on surfaces from a set of depth maps. Based on a local graphbased structure, where each local graph spans one depth map, our algorithm is able to compute partial Voronoi diagrams (one per scan), and then to merge/update them into a single and globally consistent Voronoi diagram. Our first results show that this algorithm is particularly promising for improving the sampling quality of massive point clouds or for reconstructing very large-scale scenes, with low and manageable memory consumption.
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    Towards the Reconstruction of Wide Historical Sites: A Local Graph-based Representation to Resample Gigantic Acquisitions
    (The Eurographics Association, 2018) Bletterer, Arnaud; Payan, Frédéric; Antonini, Marc; Meftah, Anis; Sablatnig, Robert and Wimmer, Michael
    Nowadays, LiDAR scanners are able to digitize very wide historical sites, leading to point clouds composed of billions of points. These point clouds are able to describe very small objects or elements disseminated in these sites, but also exhibit numerous defects in terms of sampling quality. Moreover, they sometimes contain too many samples to be processed as they are. In this paper, we propose a local graph-based structure to deal with the set of LiDAR acquisitions of a digitization campaign. Each acquisition is considered as a graph representing the local behavior of the captured surface. Those local graphs are then connected together to obtain a single and global representation of the original scene. This structure is particularly suitable for resampling gigantic points clouds. We show how we can reduce the number of points drastically while preserving the visual quality of large and complex sites, whatever the number of acquisitions.