Replaceable Substructures for Efficient Part-Based Modeling

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dc.contributor.authorLiu, Hanen_US
dc.contributor.authorVimont, Ulysseen_US
dc.contributor.authorWand, Michaelen_US
dc.contributor.authorCani, Marie-Pauleen_US
dc.contributor.authorHahmann, Stefanieen_US
dc.contributor.authorRohmer, Damienen_US
dc.contributor.authorMitra, Niloy J.en_US
dc.contributor.editorOlga Sorkine-Hornung and Michael Wimmeren_US
dc.date.accessioned2015-04-16T07:45:44Z
dc.date.available2015-04-16T07:45:44Z
dc.date.issued2015en_US
dc.description.abstractA popular mode of shape synthesis involves mixing and matching parts from different objects to form a coherent whole. The key challenge is to efficiently synthesize shape variations that are plausible, both locally and globally. A major obstacle is to assemble the objects with local consistency, i.e., all the connections between parts are valid with no dangling open connections. The combinatorial complexity of this problem limits existing methods in geometric and/or topological variations of the synthesized models. In this work, we introduce replaceable substructures as arrangements of parts that can be interchanged while ensuring boundary consistency. The consistency information is extracted from part labels and connections in the original source models. We present a polynomial time algorithm that discovers such substructures by working on a dual of the original shape graph that encodes inter-part connectivity. We demonstrate the algorithm on a range of test examples producing plausible shape variations, both from a geometric and from a topological viewpoint.en_US
dc.description.number2en_US
dc.description.sectionheadersShape Collectionsen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume34en_US
dc.identifier.doi10.1111/cgf.12579en_US
dc.identifier.pages503-513en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12579en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleReplaceable Substructures for Efficient Part-Based Modelingen_US
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