Bag of Words and Local Spectral Descriptor for 3D Partial Shape Retrieval

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dc.contributor.authorLavoué, Guillaumeen_US
dc.contributor.editorH. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkampen_US
dc.date.accessioned2013-04-25T14:10:26Z
dc.date.available2013-04-25T14:10:26Z
dc.date.issued2011en_US
dc.description.abstractThis paper presents a 3D shape retrieval algorithm based on the Bag of Words (BoW) paradigm. For a given 3D shape, the proposed approach considers a set of feature points uniformly sampled on the surface and associated with local Fourier descriptors; this descriptor is computed in the neighborhood of each feature point by projecting the geometry onto the eigenvectors of the Laplace-Beltrami operator, it is highly discriminative, robust to connectivity and geometry changes and also fast to compute. In a preliminary step, a visual dictionary is built by clustering a large set of feature descriptors, then each 3D shape is described by an histogram of occurrences of these visual words. The performances of our approach have been compared against very recent state-of-theart methods on several different datasets. For global shape retrieval our approach is comparable to these recent works, however it clearly outperforms them in the case of partial shape retrieval.en_US
dc.description.sectionheadersLocal Shape Descriptorsen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-31-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR11/041-048en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-H.3.3 [Information Storage and Retrieval]: Information Search and Retrievalen_US
dc.titleBag of Words and Local Spectral Descriptor for 3D Partial Shape Retrievalen_US
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