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dc.contributor.authorDutagaci, H.en_US
dc.contributor.authorGodil, A.en_US
dc.contributor.authorDaras, P.en_US
dc.contributor.authorAxenopoulos, A.en_US
dc.contributor.authorLitos, G.en_US
dc.contributor.authorManolopoulou, S.en_US
dc.contributor.authorGoto, K.en_US
dc.contributor.authorYanagimachi, T.en_US
dc.contributor.authorKurita, Y.en_US
dc.contributor.authorKawamura, S.en_US
dc.contributor.authorFuruya, T.en_US
dc.contributor.authorOhbuchi, R.en_US
dc.contributor.editorH. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkampen_US
dc.date.accessioned2013-04-25T14:10:27Z
dc.date.available2013-04-25T14:10:27Z
dc.date.issued2011en_US
dc.identifier.isbn978-3-905674-31-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttp://dx.doi.org/10.2312/3DOR/3DOR11/065-069en_US
dc.description.abstractIn this paper we present the results of the 3D Shape Retrieval Contest 2011 (SHREC'11) track on generic shape retrieval. The aim of this track is to evaluate the performance of 3D shape retrieval algorithms that can operate on arbitrary 3D models. The benchmark dataset consists of 1000 3D objects classified in 50 categories. The 3D models are mainly classified based on visual shape similarity and each class has equal number of models to reduce the possible bias in evaluation results. Two groups have participated in the track with six methods in total.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.5.4 [Pattern Recognition]: Applications-Computer vision; H.3.3 [Computer Graphics]: Information Systems-Information Search and Retrievalen_US
dc.titleSHREC '11 Track: Generic Shape Retrievalen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.description.sectionheadersShape Retrieval Evaluation Contest (SHREC 2011)en_US


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