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dc.contributor.authorSipiran, I.en_US
dc.contributor.authorMeruane, R.en_US
dc.contributor.authorBustos, B.en_US
dc.contributor.authorSchreck, Tobiasen_US
dc.contributor.authorJohan, H.en_US
dc.contributor.authorLi, B.en_US
dc.contributor.authorLu, Y.en_US
dc.contributor.editorUmberto Castellani and Tobias Schreck and Silvia Biasotti and Ioannis Pratikakis and Afzal Godil and Remco Veltkampen_US
dc.date.accessioned2013-09-24T12:04:08Z
dc.date.available2013-09-24T12:04:08Z
dc.date.issued2013en_US
dc.identifier.isbn978-3-905674-44-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttp://dx.doi.org/10.2312/3DOR/3DOR13/081-088en_US
dc.description.abstractPartial shape retrieval is a challenging problem in content-based 3D model retrieval. This track intends to evaluate the performance of existing algorithms for partial retrieval. The contest is based on a new large-scale query set obtained by mimicking the range image acquisition using a standard 3D benchmark as target set. The query set contains 7200 partial meshes with different levels of complexity. Furthermore, we propose the use of new performance measures based on a partiality factor. With this characteristics, our goal is to evaluate several important aspects: effectiveness, efficiency, robustness and scalability. The obtained results of this track open new questions regarding the difficulty of the partial shape retrieval problem and the scalability of algorithms. In addition, potential future directions on this topic are identified.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.3.2 [Information storage and retrieval]en_US
dc.subjectInformation Search and Retrievalen_US
dc.subjectRetrieval modelsen_US
dc.subjectI.2.10 [Artificial Intelligence]en_US
dc.subjectVision and Scene Understandingen_US
dc.subjectShapeen_US
dc.titleSHREC'13 Track: Large-Scale Partial Shape Retrieval Using Simulated Range Imagesen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.description.sectionheadersSHREC Track Reportsen_US


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