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dc.date.accessioned2022-03-25T17:59:08Z
dc.date.available2023-10-01T22:45:51Z
dc.date.created2022-02-15T19:37:24Z
dc.date.issued2022
dc.identifier.citationRomanengo, Chiara Raffo, Andrea Qie, Yifan Anwer, Nabil Falcidieno, Bianca . Fit4CAD: A point cloud benchmark for fitting simple geometric primitives in CAD objects. Computers & graphics. 2021
dc.identifier.urihttp://hdl.handle.net/10852/92925
dc.description.abstractWe propose Fit4CAD, a benchmark for the evaluation and comparison of methods for fitting simple geometric primitives in point clouds representing CAD objects. This benchmark is meant to help both method developers and those who want to identify the best performing tools. The Fit4CAD dataset is composed by 225 high quality point clouds, each of which has been obtained by sampling a CAD object. The way these elements were created by using existing platforms and datasets makes the benchmark easily expandable. The dataset is already split into a training set and a test set. To assess performance and accuracy of the different primitive fitting methods, various measures are defined. To demonstrate the effective use of Fit4CAD, we have tested it on two methods belonging to two different categories of approaches to the primitive fitting problem: a clustering method based on a primitive growing framework and a parametric method based on the Hough transform.
dc.languageEN
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleFit4CAD: A point cloud benchmark for fitting simple geometric primitives in CAD objects
dc.typeJournal article
dc.creator.authorRomanengo, Chiara
dc.creator.authorRaffo, Andrea
dc.creator.authorQie, Yifan
dc.creator.authorAnwer, Nabil
dc.creator.authorFalcidieno, Bianca
cristin.unitcode185,15,13,0
cristin.unitnameMatematisk institutt
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.cristin2002048
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Computers & graphics&rft.volume=&rft.spage=&rft.date=2021
dc.identifier.jtitleComputers & graphics
dc.identifier.volume102
dc.identifier.startpage133
dc.identifier.endpage143
dc.identifier.pagecount0
dc.identifier.doihttps://doi.org/10.1016/j.cag.2021.09.013
dc.identifier.urnURN:NBN:no-95495
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0097-8493
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/92925/1/2105.06858.pdf
dc.type.versionAcceptedVersion


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Attribution-NonCommercial-NoDerivatives 4.0 International
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