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dc.contributor.authorde Medeiros Esper, Ian
dc.contributor.authorCordova-Lopez, Luis Eduardo
dc.contributor.authorRomanov, Dmytro
dc.contributor.authorAlvseike, Ole
dc.contributor.authorFrom, Pål Johan
dc.contributor.authorMason, Alex
dc.date.accessioned2022-03-10T08:25:32Z
dc.date.available2022-03-10T08:25:32Z
dc.date.created2022-02-26T12:20:56Z
dc.date.issued2022
dc.identifier.citationData in Brief. 2022, 41 .
dc.identifier.issn2352-3409
dc.identifier.urihttps://hdl.handle.net/11250/2984147
dc.description.abstractThis paper presents a pig carcass cutting dataset, captured from a bespoke frame structure with 6 Intel® RealSense™ Depth Camera D415 cameras attached, and later recorded from a single camera attached to a robotic arm cycling through the positions previously defined by the frame structure. The data is composed of bags files recorded from the Intel’s SDK, which includes RGB-D data and camera intrinsic parameters for each sensor. In addition, ten JSON files with the transformation matrix for each camera in relation to the left/front camera in the structure are provided, five JSON files for the data recorded with the bespoke frame and five JSON files for the data captured with the robotic arm.
dc.language.isoeng
dc.titlePigs: A stepwise RGB-D novel pig carcass cutting dataset
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionacceptedVersion
dc.source.pagenumber9
dc.source.volume41
dc.source.journalData in Brief
dc.identifier.doi10.1016/j.dib.2022.107945
dc.identifier.cristin2005650
dc.relation.projectEC/H2020/871631
dc.relation.projectNorges forskningsråd: 281234
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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