VMV18

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https://diglib.eg.org/handle/10.2312/2632666

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Browsing VMV18 by Subject "based models"

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    Hierarchical Additive Poisson Disk Sampling
    (The Eurographics Association, 2018) Dieckmann, Alexander; Klein, Reinhard; Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip
    Generating samples of point clouds and meshes with blue noise characteristics is desirable for many applications in rendering and geometry processing. Working with laser-scanned or lidar point clouds, we usually find region with artifacts called scanlines and scan-edges. These regions are problematic for geometry processing applications, since it is not clear how many points should be selected to define a proper neighborhood. We present a method to construct a hierarchical additive poisson disk sampling from densely sampled point sets, which yield better point neighborhoods. It can be easily implemented using an octree data structure where each octree node contains a grid, called Modifiable Nested Octree [Sch14]. The generation of the sampling amounts to distributing the points over a hierarchy (octree) of resolution levels (grids) in a greedy manner. Propagating the distance constraint r through the hierarchy while drawing samples from the point set leads to a hierarchy of well distributed, random samplings. This ensures that in a disk with radius r, around a point, no other point upwards in the hierarchy is found. The sampling is additive in the sense that the union of points sets up to a certain hierarchy depth D is a poisson disk sampling. This makes it easy to select a resolution where the scan-artifacts have a lower impact on the processing result. The generated sampling can be made sensitive to surface features by a simple preprocessing step, yielding high quality low resolution poisson samplings of point clouds.