Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.image.2010.10.006
DC FieldValue
dc.title3D model retrieval using weighted bipartite graph matching
dc.contributor.authorGao, Y.
dc.contributor.authorDai, Q.
dc.contributor.authorWang, M.
dc.contributor.authorZhang, N.
dc.date.accessioned2013-07-04T07:31:40Z
dc.date.available2013-07-04T07:31:40Z
dc.date.issued2011
dc.identifier.citationGao, Y., Dai, Q., Wang, M., Zhang, N. (2011). 3D model retrieval using weighted bipartite graph matching. Signal Processing: Image Communication 26 (1) : 39-47. ScholarBank@NUS Repository. https://doi.org/10.1016/j.image.2010.10.006
dc.identifier.issn09235965
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/38999
dc.description.abstractIn this paper, we propose a view-based 3D model retrieval algorithm, where many-to-many matching method, weighted bipartite graph matching, is employed for comparison between two 3D models. In this work, each 3D model is represented by a set of 2D views. Representative views are first selected from the query model and the corresponding initial weights are provided. These initial weights are further updated based on the relationship among these representative views. The weighted bipartite graph is built with these selected 2D views, and the matching result is used to measure the similarity between two 3D models. Experimental results and comparison with existing methods show the effectiveness of the proposed algorithm. © 2010 ElsevierB.V.Allrightsreserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.image.2010.10.006
dc.sourceScopus
dc.subject3D model retrieval
dc.subjectRandom walk
dc.subjectWeighted bipartite graph matching
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1016/j.image.2010.10.006
dc.description.sourcetitleSignal Processing: Image Communication
dc.description.volume26
dc.description.issue1
dc.description.page39-47
dc.description.codenSPICE
dc.identifier.isiut000286711700004
Appears in Collections:Staff Publications

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