Une approche basée graphes pour la modélisation et le traitement de nuages de points massifs issus d’acquisitions de LiDARs terrestres

Abstract : With the evolution of 3D acquisition devices, point clouds have now become an essential representation of digitized scenes. Recent systems are able to capture several hundreds of millions of points in a single acquisition. As multiple acquisitions are necessary to capture the geometry of large-scale scenes, a historical site for example, we obtain massive point clouds, i.e., composed of billions of points. In this thesis, we are interested in the structuration and manipulation of point clouds from acquisitions generated by terrestrial LiDARs. From the structure of each acquisition, graphs, each representing the local connectivity of the digitized surface, are constructed. Created graphs are then linked together to obtain a global representation of the captured surface. We show that this structure is particularly adapted to the manipulation of the underlying surface of massive point clouds, even on computers with limited memory. Especially, we show that this structure allow to deal with two problems specific to that kind of data. A first one linked to the resampling of point clouds, by generating distributions of good quality in terms of blue noise thanks to a Poisson disk sampling algorithm. Another one connected to the construction of centroidal Voronoi tessellations, allowing to enhance the quality of generated distributions and to reconstruct triangular meshes.
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Arnaud Bletterer. Une approche basée graphes pour la modélisation et le traitement de nuages de points massifs issus d’acquisitions de LiDARs terrestres. Traitement du signal et de l'image [eess.SP]. Université Côte d'Azur, 2018. Français. ⟨NNT : 2018AZUR4218⟩. ⟨tel-02099777⟩

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