Anisotropic Spectral Manifold Wavelet Descriptor for Deformable Shape Analysis and Matching

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dc.contributor.authorLi, Qinsongen_US
dc.contributor.authorLiu, Shengjunen_US
dc.contributor.authorHu, Lingen_US
dc.contributor.authorLiu, Xinruen_US
dc.contributor.editorFu, Hongbo and Ghosh, Abhijeet and Kopf, Johannesen_US
dc.date.accessioned2018-10-07T14:32:06Z
dc.date.available2018-10-07T14:32:06Z
dc.date.issued2018
dc.description.abstractIn this paper, we present a novel framework termed Anisotropic Spectral Manifold Wavelet Transform (ASMWT) for shape analysis. ASMWT comprehensively analyzes the signals from multiple directions on local manifold regions of the shape with a series of low-pass and band-pass frequency filters in each direction. Using the ASMWT coefficients of a very simple function, we efficiently construct a localizable and discriminative multiscale point descriptor, named as the Anisotropic Spectral Manifold Wavelet Descriptor (ASMWD). Since the filters used in our descriptor are direction-sensitive and able to robustly reconstruct the signals with a finite number of scales, it makes our descriptor be intrinsic-symmetry unambiguous, compact as well as efficient. The extensive experimental results demonstrate that our method achieves significant performance than several state-of-the-art methods when applied in vertex-wise shape matching.en_US
dc.description.sectionheadersSkeleton and Deformation
dc.description.seriesinformationPacific Graphics Short Papers
dc.identifier.doi10.2312/pg.20181276
dc.identifier.isbn978-3-03868-073-4
dc.identifier.pages41-44
dc.identifier.urihttps://doi.org/10.2312/pg.20181276
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pg20181276
dc.publisherThe Eurographics Associationen_US
dc.titleAnisotropic Spectral Manifold Wavelet Descriptor for Deformable Shape Analysis and Matchingen_US
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