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dc.identifier.urihttp://hdl.handle.net/1951/60261
dc.identifier.urihttp://hdl.handle.net/11401/71527
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeThesis
dcterms.abstractThis thesis presents a new paradigm for non-rigid 3D shape retrieval, which is also called Bag of Feature Graphs (BoFG). The main idea is to connect only the features on the shape to construct the graphs so that the number of points involved in the computation is greatly reduced. Given a vocabulary of geometric words, the BoFG approach generates a graph that preserves the spatial information among features for each word. The spatial information is weighted by its similarities to each word so that points unlike the word category are eliminated. And the graphs are captured by the affinity matrices of Weighted Heat Kernels (WHK) whose eigenvalues form a shape descriptor. Also, the BoFG approach can supports partial 3D shape retrieval by coupling with graph matching techniques and comparing only sub graphs that represent common parts of the shape. Finally, experiments are conducted and show that the proposed BoFG method is faster to compute and the retrieval performance is also competitive compared with other state-of-the-art methods.
dcterms.available2013-05-24T16:38:19Z
dcterms.available2015-04-24T14:47:49Z
dcterms.contributorQin, Hongen_US
dcterms.contributorGu, Xianfengen_US
dcterms.contributorMueller, Klaus.en_US
dcterms.creatorHOU, XIAOHUA
dcterms.dateAccepted2013-05-24T16:38:19Z
dcterms.dateAccepted2015-04-24T14:47:49Z
dcterms.dateSubmitted2013-05-24T16:38:19Z
dcterms.dateSubmitted2015-04-24T14:47:49Z
dcterms.descriptionDepartment of Computer Scienceen_US
dcterms.extent68 pg.en_US
dcterms.formatMonograph
dcterms.formatApplication/PDFen_US
dcterms.identifierhttp://hdl.handle.net/1951/60261
dcterms.identifierhttp://hdl.handle.net/11401/71527
dcterms.issued2012-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2013-05-24T16:38:19Z (GMT). No. of bitstreams: 1 StonyBrookUniversityETDPageEmbargo_20130517082608_116839.pdf: 41286 bytes, checksum: 425a156df10bbe213bfdf4d175026e82 (MD5) Previous issue date: 1en
dcterms.provenanceMade available in DSpace on 2015-04-24T14:47:49Z (GMT). No. of bitstreams: 3 StonyBrookUniversityETDPageEmbargo_20130517082608_116839.pdf.jpg: 1934 bytes, checksum: c116f0e1e7be19420106a88253e31f2e (MD5) StonyBrookUniversityETDPageEmbargo_20130517082608_116839.pdf.txt: 336 bytes, checksum: 84c0f8f99f2b4ae66b3cc3ade09ad2e9 (MD5) StonyBrookUniversityETDPageEmbargo_20130517082608_116839.pdf: 41286 bytes, checksum: 425a156df10bbe213bfdf4d175026e82 (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectComputer science
dcterms.titleBag of Feature Graphs: A New Method for Non-rigid 3D Shape Retrieval
dcterms.typeThesis


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