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    Multi-Scale Point Cloud Analysis
    (The Eurographics Association, 2019) Lejemble, Thibault; Mura, Claudio; Barthe, Loïc; Mellado, Nicolas; Fusiello, Andrea and Bimber, Oliver
    Surfaces sampled with point clouds often exhibit multi-scale properties due to the high variation between their feature size. Traditional shape analysis techniques usually rely on geometric descriptors able to characterize a point and its close neighborhood at multiple scale using smoothing kernels of varying radii. We propose to add a spatial regularization to these point-wise descriptors in two different ways. The first groups similar points in regions that are structured in a hierarchical graph. The graph is then simplified and processed to extract pertinent regions. The second performs a spatial gradient descent in order to highlight stable parts of the surface. We show two experiments focusing on planar and anisotropic feature areas respectively.