Local Goemetrical Feature with Spatial Context for Shape-based 3D Model Retrieval

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dc.contributor.authorKawamura, Shunen_US
dc.contributor.authorUsui, Kazuyaen_US
dc.contributor.authorFuruya, Takahikoen_US
dc.contributor.authorOhbuchi, Ryutarouen_US
dc.contributor.editorM. Spagnuolo and M. Bronstein and A. Bronstein and A. Ferreiraen_US
dc.date.accessioned2013-09-24T10:53:06Z
dc.date.available2013-09-24T10:53:06Z
dc.date.issued2012en_US
dc.description.abstractWith recent popularity of 3D models, retrieval and recognition of 3D models based on their shape has become an important subject of study. This paper proposes a 3D model retrieval algorithm that is invariant to global deformation as well as to similarity transformation of 3D models. The algorithm is based on a set of local 3D geometrical features combined with bag-of-features approach. The algorithm employs a novel local feature, which is a combination of local geometrical feature enhanced with its spatial context computed as histogram of diffusion distance computed over mesh surface. Experimental evaluation of retrieval accuracy by using benchmark databases showed that adding positional context significantly improves retrieval accuracy.en_US
dc.description.sectionheadersPostersen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-36-1en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR12/055-058en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing, I.3.m [Computer Graphics]: Miscellaneousen_US
dc.titleLocal Goemetrical Feature with Spatial Context for Shape-based 3D Model Retrievalen_US
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