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dc.contributor.authorGarro, Valeriaen_US
dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.editorBenjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkampen_US
dc.date.accessioned2014-12-15T13:52:04Z
dc.date.available2014-12-15T13:52:04Z
dc.date.issued2014en_US
dc.identifier.isbn978-3-905674-58-3en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttp://dx.doi.org/10.2312/3dor.20141045en_US
dc.identifier.urihttp://hdl.handle.net/10.2312/3dor.20141045.017-024
dc.description.abstractIn this paper we present a new method for shape description and matching based on a tree representation built upon the scale space analysis of maxima of the Autodiffusion function (ADF). The use of the Heat Kernel based approach makes the method invariant to articulated deformations. By coupling maxima of the Autodiffusion function with the related basins of attraction, it is possible to link the information at different scales encoding spatial relationships in a tree structure. Furthermore, texture information can be easily included in the descriptor by adding regional color histograms to the node attributes of the tree. Dedicated graph kernels have been designed to evaluate shape dissimilarity from the obtained representations using both structural, geometric and color information. Preliminary experiments performed on the SHREC 2013 non-rigid textured dataset showed very good retrieval performances.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.3.1 [Computer Graphics]en_US
dc.subjectInformation Storage and Retrievalen_US
dc.subjectContent Analysis and Indexingen_US
dc.titleTreeSha: 3D Shape Retrieval with a Tree Graph Representation based on the Autodiffusion Function Topologyen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US


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