Dutta, SomnathRussig, BenjaminGumhold, StefanBanterle, FrancescoCaggianese, GiuseppeCapece, NicolaErra, UgoLupinetti, KatiaManfredi, Gilda2023-11-122023-11-122023978-3-03868-235-62617-4855https://doi.org/10.2312/stag.20231295https://diglib.eg.org:443/handle/10.2312/stag20231295We present a GPU-accelerated global registration method for registering partial shapes, a common and often performancecritical task in many robotics, vision, and graphics applications. Global registration based on descriptor matching is highly dependent on the quality at which a shape is sampled, and computing expressive descriptors typically incurs high computation time. In this paper, we augment a global pair-wise registration algorithm based on hierarchical shape descriptors with a GPU-accelerated descriptor construction process, reducing the time spent on building descriptors by an order of magnitude. This allows for building more expressive descriptors, achieving a dual gain in both performance and accuracy. We conducted extensive evaluations on a large set of pair-wise registration problems, demonstrating very competitive registration accuracy, often rendering subsequent refinement with a local method unnecessary.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies -> Computer Graphics;Shape Modeling; Point-based modelsComputing methodologiesComputer GraphicsShape ModelingPointbased models10.2312/stag.2023129559-6911 pages