Coverage Axis: Inner Point Selection for 3D Shape Skeletonization

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dc.contributor.authorDou, Zhiyangen_US
dc.contributor.authorLin, Chengen_US
dc.contributor.authorXu, Ruien_US
dc.contributor.authorYang, Leien_US
dc.contributor.authorXin, Shiqingen_US
dc.contributor.authorKomura, Takuen_US
dc.contributor.authorWang, Wenpingen_US
dc.contributor.editorChaine, Raphaëlleen_US
dc.contributor.editorKim, Min H.en_US
dc.date.accessioned2022-04-22T06:29:17Z
dc.date.available2022-04-22T06:29:17Z
dc.date.issued2022
dc.description.abstractIn this paper, we present a simple yet effective formulation called Coverage Axis for 3D shape skeletonization. Inspired by the set cover problem, our key idea is to cover all the surface points using as few inside medial balls as possible. This formulation inherently induces a compact and expressive approximation of the Medial Axis Transform (MAT) of a given shape. Different from previous methods that rely on local approximation error, our method allows a global consideration of the overall shape structure, leading to an efficient high-level abstraction and superior robustness to noise. Another appealing aspect of our method is its capability to handle more generalized input such as point clouds and poor-quality meshes. Extensive comparisons and evaluations demonstrate the remarkable effectiveness of our method for generating compact and expressive skeletal representation to approximate the MAT.en_US
dc.description.number2
dc.description.sectionheadersTopology
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14484
dc.identifier.issn1467-8659
dc.identifier.pages419-432
dc.identifier.pages14 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14484
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14484
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies --> Shape analysis
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.titleCoverage Axis: Inner Point Selection for 3D Shape Skeletonizationen_US
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