Evocube: A Genetic Labelling Framework for Polycube‐Maps

dc.contributor.authorDumery, C.en_US
dc.contributor.authorProtais, F.en_US
dc.contributor.authorMestrallet, S.en_US
dc.contributor.authorBourcier, C.en_US
dc.contributor.authorLedoux, F.en_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2022-10-11T05:24:59Z
dc.date.available2022-10-11T05:24:59Z
dc.date.issued2022
dc.description.abstractPolycube‐maps are used as base‐complexes in various fields of computational geometry, including the generation of regular all‐hexahedral meshes free of internal singularities. However, the strict alignment constraints behind polycube‐based methods make their computation challenging for CAD models used in numerical simulation via finite element method (FEM). We propose a novel approach based on an evolutionary algorithm to robustly compute polycube‐maps in this context.We address the labelling problem, which aims to precompute polycube alignment by assigning one of the base axes to each boundary face on the input. Previous research has described ways to initialize and improve a labelling via greedy local fixes. However, such algorithms lack robustness and often converge to inaccurate solutions for complex geometries. Our proposed framework alleviates this issue by embedding labelling operations in an evolutionary heuristic, defining fitness, crossover, and mutations in the context of labelling optimization. We evaluate our method on a thousand smooth and CAD meshes, showing Evocube converges to accurate labellings on a wide range of shapes. The limitations of our method are also discussed thoroughly.en_US
dc.description.number6
dc.description.sectionheadersMajor Revision from Eurographics Conference
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14649
dc.identifier.issn1467-8659
dc.identifier.pages467-479
dc.identifier.urihttps://doi.org/10.1111/cgf.14649
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14649
dc.publisher© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjectgenetic algorithms
dc.subjectmodelling
dc.subjectmesh generation
dc.subjectmethods and applications
dc.titleEvocube: A Genetic Labelling Framework for Polycube‐Mapsen_US
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