EG2023

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Parameter-Free and Improved Connectivity for Point Clouds
(The Eurographics Association, 2023) Marin, Diana; Ohrhallinger, Stefan; Wimmer, Michael; Singh, Gurprit; Chu, Mengyu (Rachel)
Determining connectivity in unstructured point clouds is a long-standing problem that is still not addressed satisfactorily. In this poster, we propose an extension to the proximity graph introduced in [MOW22] to three-dimensional models. We use the spheres-of-influence (SIG) proximity graph restricted to the 3D Delaunay graph to compute connectivity between points. Our approach shows a better encoding of the connectivity in relation to the ground truth than the k-nearest neighborhood (kNN) for a wide range of k values, and additionally, it is parameter-free. Our result for this fundamental task offers potential for many applications relying on kNN, e.g., improvements in normal estimation, surface reconstruction, motion planning, simulations, and many more.