Retrieval and Classification on Textured 3D Models

dc.contributor.authorBiasotti, S.en_US
dc.contributor.authorCerri, A.en_US
dc.contributor.authorAbdelrahman, M.en_US
dc.contributor.authorAono, M.en_US
dc.contributor.authorHamza, A. Benen_US
dc.contributor.authorEl-Melegy, M.en_US
dc.contributor.authorFarag, A.en_US
dc.contributor.authorGarro, V.en_US
dc.contributor.authorGiachetti, A.en_US
dc.contributor.authorGiorgi, D.en_US
dc.contributor.authorGodil, A.en_US
dc.contributor.authorLi, C.en_US
dc.contributor.authorLiu, Y.-J.en_US
dc.contributor.authorMartono, H. Y.en_US
dc.contributor.authorSanada, C.en_US
dc.contributor.authorTatsuma, A.en_US
dc.contributor.authorVelasco-Forero, S.en_US
dc.contributor.authorXu, C.-X.en_US
dc.contributor.editorBenjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkampen_US
dc.date.accessioned2014-12-15T13:52:10Z
dc.date.available2014-12-15T13:52:10Z
dc.date.issued2014en_US
dc.description.abstractThis paper reports the results of the SHREC'14 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 572 textured mesh models, having a two-level classification based on geometry and texture. Together with the dataset, a training set of 96 models was provided. The track saw eight participants and the submission of 22 runs, to either the retrieval or the classification contest, or both. The evaluation results show a promising scenario about textured 3D retrieval methods, and reveal interesting insights in dealing with texture information in the CIELab rather than in the RGB colour space.en_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-58-3en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3dor.20141057en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/3dor.20141057.111-120
dc.publisherThe Eurographics Associationen_US
dc.subjectH.3.1 [Information Storage and Retrieval]en_US
dc.subjectContent Analysis and Indexingen_US
dc.subjectAbstracting methodsen_US
dc.titleRetrieval and Classification on Textured 3D Modelsen_US
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