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dc.contributor.authorWang, Wenchengen_US
dc.contributor.authorMa, Junhuien_US
dc.contributor.authorXu, Panpanen_US
dc.contributor.authorChu, Yiyaoen_US
dc.contributor.editorLee, Jehee and Theobalt, Christian and Wetzstein, Gordonen_US
dc.description.abstractThe existing methods for intrinsic symmetry detection on 3D models always need complex measures such as geodesic distances for describing intrinsic geometry and statistical computation for finding non-rigid transformations to associate symmetrical shapes. They are expensive, may miss symmetries, and cannot guarantee their obtained symmetrical parts in high quality. We observe that only extrinsic symmetries exist between convex shapes, and two intrinsically symmetric shapes can be determined if their belonged convex sub-shapes are symmetrical to each other correspondingly and connected in a similar topological structure. Thus, we propose to decompose the model into convex parts, and use the similar structures of the skeleton of the model to guide combination of extrinsic symmetries between convex parts for intrinsic symmetry detection. In this way, we give up statistical computation for intrinsic symmetry detection, and avoid complex measures for describing intrinsic geometry. With the similar structures being from small to large gradually, we can quickly detect multi-scale partial intrinsic symmetries in a bottom up manner. Benefited from the well segmented convex parts, our obtained symmetrical parts are in high quality. Experimental results show that our method can find many more symmetries and runs much faster than the existing methods, even by several orders of magnitude.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectMesh models
dc.subjectShape analysis
dc.subjectAdditional Key Words
dc.subjectsymmetry detection
dc.subjectpartial intrinsic symmetry
dc.titleIntrinsic Symmetry Detection on 3D Models with Skeleton-guided Combination of Extrinsic Symmetriesen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersShape Analysis

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  • 38-Issue 7
    Pacific Graphics 2019 - Symposium Proceedings

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