PaMO: Parallel Mesh Optimization for Intersection-Free Low-Poly Modeling on the GPU

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dc.contributor.authorOh, Seonghunen_US
dc.contributor.authorYuan, Xiaodien_US
dc.contributor.authorWei, Xinyueen_US
dc.contributor.authorShi, Ruoxien_US
dc.contributor.authorXiang, Fanboen_US
dc.contributor.authorLiu, Minghuaen_US
dc.contributor.authorSu, Haoen_US
dc.contributor.editorChristie, Marcen_US
dc.contributor.editorPietroni, Nicoen_US
dc.contributor.editorWang, Yu-Shuenen_US
dc.date.accessioned2025-10-07T05:03:22Z
dc.date.available2025-10-07T05:03:22Z
dc.date.issued2025
dc.description.abstractReducing the triangle count in complex 3D models is a basic geometry preprocessing step in graphics pipelines such as efficient rendering and interactive editing. However, most existing mesh simplification methods exhibit a few issues. Firstly, they often lead to self-intersections during decimation, a major issue for applications such as 3D printing and soft-body simulation. Second, to perform simplification on a mesh in the wild, one would first need to perform re-meshing, which often suffers from surface shifts and losses of sharp features. Finally, existing re-meshing and simplification methods can take minutes when processing large-scale meshes, limiting their applications in practice. To address the challenges, we introduce a novel GPUbased mesh optimization approach containing three key components: (1) a parallel re-meshing algorithm to turn meshes in the wild into watertight, manifold, and intersection-free ones, and reduce the prevalence of poorly shaped triangles; (2) a robust parallel simplification algorithm with intersection-free guarantees; (3) an optimization-based safe projection algorithm to realign the simplified mesh with the input, eliminating the surface shift introduced by re-meshing and recovering the original sharp features. The algorithm demonstrates remarkable efficiency, simplifying a 2-million-face mesh to 20k triangles in 3 seconds on RTX4090. We evaluated the approach on the Thingi10K dataset and showcased its exceptional performance in geometry preservation and speed. https://seonghunn.github.io/pamo/en_US
dc.description.number7
dc.description.sectionheadersShape Extraction
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume44
dc.identifier.doi10.1111/cgf.70267
dc.identifier.issn1467-8659
dc.identifier.pages16 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.70267
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf70267
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies → Mesh geometry models
dc.subjectComputing methodologies → Mesh geometry models
dc.titlePaMO: Parallel Mesh Optimization for Intersection-Free Low-Poly Modeling on the GPUen_US
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