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dc.contributor.authorRodolà, E.en_US
dc.contributor.authorMoeller, M.en_US
dc.contributor.authorCremers, D.en_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2018-01-10T07:43:28Z
dc.date.available2018-01-10T07:43:28Z
dc.date.issued2017
dc.identifier.issn1467-8659
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.13160
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13160
dc.description.abstractThe concept of using functional maps for representing dense correspondences between deformable shapes has proven to be extremely effective in many applications. However, despite the impact of this framework, the problem of recovering the point‐to‐point correspondence from a given functional map has received surprisingly little interest. In this paper, we analyse the aforementioned problem and propose a novel method for reconstructing pointwise correspondences from a given functional map. The proposed algorithm phrases the matching problem as a regularized alignment problem of the spectral embeddings of the two shapes. Opposed to established methods, our approach does not require the input shapes to be nearly‐isometric, and easily extends to recovering the point‐to‐point correspondence in part‐to‐whole shape matching problems. Our numerical experiments demonstrate that the proposed approach leads to a significant improvement in accuracy in several challenging cases.The concept of using functional maps for representing dense correspondences between deformable shapes has proven to be extremely effective in many applications. However, despite the impact of this framework, the problem of recovering the point‐to‐point correspondence from a given functional map has received surprisingly little interest. In this paper, we analyse the aforementioned problem and propose a novel method for reconstructing pointwise correspondences from a given functional map. The proposed algorithm phrases the matching problem as a regularized alignment problem of the spectral embeddings of the two shapes. Opposed to established methods, our approach does not require the input shapes to be nearly‐isometric, and easily extends to recovering the point‐to‐point correspondence in part‐to‐whole shape matching problems.en_US
dc.publisher© 2017 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subject3D shape matching
dc.subjectI.3.5 [Computer Graphics]: Computational Geometry and Object Modelling—Shape Analysis
dc.titleRegularized Pointwise Map Recovery from Functional Correspondenceen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersArticles
dc.description.volume36
dc.description.number8
dc.identifier.doi10.1111/cgf.13160
dc.identifier.pages700-711


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