{"dcterms:modified":"2024-03-19","dcterms:creator":"DataverseNO","@type":"ore:ResourceMap","@id":"https://dataverse.no/api/datasets/export?exporter=OAI_ORE&persistentId=https://doi.org/10.18710/VIJXTL","ore:describes":{"citation:dsDescription":{"citation:dsDescriptionValue":"Replication Data in the form of a Robot Operating System (ROS) recording (ROS-bag) to replicate the results of the paper \"Automatic Calibration of an Industrial RGB-D Camera Network using Retroreflective Fiducial Markers.\" The contents of the dataset are timestamped images and point clouds recorded from six different sensor nodes.","citation:dsDescriptionDate":"2019-01-31"},"citation:keyword":[{"citation:keywordValue":"RGB-D"},{"citation:keywordValue":"Vision"},{"citation:keywordValue":"Point cloud"},{"citation:keywordValue":"Registration"},{"citation:keywordValue":"Calibration"}],"citation:datasetContact":{"citation:datasetContactName":"Aalerud, Atle","citation:datasetContactAffiliation":"University of Agder","citation:datasetContactEmail":"atle.aalerud@gmail.com"},"citation:producer":{"citation:producerName":"University of Agder","citation:producerAbbreviation":"UiA","citation:producerURL":"https://www.uia.no/en"},"publication":{"publicationCitation":"Aalerud, A., Dybedal, J. & Hovland, G. (2019). Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers. Sensors, 19(7): 1561.","publicationIDType":"doi","publicationIDNumber":"10.3390/s19071561","publicationURL":"https://doi.org/10.3390/s19071561"},"citation:distributor":{"citation:distributorName":"University of Agder","citation:distributorAffiliation":"University of Agder","citation:distributorURL":"https://dataverse.no/dataverse/uia"},"author":{"citation:authorName":"Aalerud, Atle","citation:authorAffiliation":"University of Agder","authorIdentifierScheme":"ORCID","authorIdentifier":"0000-0001-6462-235X"},"title":"Replication Data for: Automatic Calibration of an Industrial RGB-D Camera Network using Retroreflective Fiducial Markers.","subject":["Engineering","Computer and Information Science"],"dateOfDeposit":"2019-01-31","citation:depositor":"Aalerud, Atle","@id":"https://doi.org/10.18710/VIJXTL","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"1.2","schema:name":"Replication Data for: Automatic Calibration of an Industrial RGB-D Camera Network using Retroreflective Fiducial Markers.","schema:dateModified":"Thu Sep 28 17:51:12 GMT 2023","schema:datePublished":"2019-01-31","schema:license":"http://creativecommons.org/publicdomain/zero/1.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":true},"schema:includedInDataCatalog":"DataverseNO","schema:isPartOf":{"schema:name":"SFI Offshore Mechatronics","@id":"https://dataverse.no/dataverse/mechatronics","schema:description":"Next generation of advanced offshore mechatronic systems for autonomous operation and condition monitoring of offshore equipment and systems under the control of land-based operation centers, to ensure safe and efficient operation in deeper water and in harsh environments. The project is funded via The Centres for Research-based Innovation scheme by the Research Council of Norway. The consortium is a mix of 17 academic and company partners. More informations can be found at the SFI Offshore Mechatronics website.","schema:isPartOf":{"schema:name":"University of Agder","@id":"https://dataverse.no/dataverse/uia","schema:isPartOf":{"schema:name":"DataverseNO","@id":"https://dataverse.no/dataverse/root"}}},"ore:aggregates":[{"schema:name":"00_ReadMe.txt","dvcore:restricted":false,"schema:version":1,"dvcore:datasetVersionId":3623,"@id":"doi:10.18710/VIJXTL/COKJ3I","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/VIJXTL/COKJ3I","@type":"ore:AggregatedResource","schema:fileFormat":"text/plain","dvcore:filesize":336,"dvcore:storageIdentifier":"S3://2002-yellow-dataverseno:168a3446ce6-9299db7e1ecb","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"fba5a3424dc0c29e5d1e3bbd2d0a2d50"}},{"schema:name":"20181214_14_11_48.bag","dvcore:restricted":false,"schema:version":1,"dvcore:datasetVersionId":3623,"@id":"doi:10.18710/VIJXTL/YER8KT","schema:sameAs":"https://dataverse.no/api/access/datafile/:persistentId?persistentId=doi:10.18710/VIJXTL/YER8KT","@type":"ore:AggregatedResource","schema:fileFormat":"application/octet-stream","dvcore:filesize":2930485210,"dvcore:storageIdentifier":"S3://2002-yellow-dataverseno:168a3439380-945b4614cc37","dvcore:rootDataFileId":-1,"dvcore:checksum":{"@type":"MD5","@value":"d46ecf988af8f85fd38ea62b1110f7c6"}}],"schema:hasPart":["doi:10.18710/VIJXTL/COKJ3I","doi:10.18710/VIJXTL/YER8KT"]},"@context":{"author":"http://purl.org/dc/terms/creator","authorIdentifier":"http://purl.org/spar/datacite/AgentIdentifier","authorIdentifierScheme":"http://purl.org/spar/datacite/AgentIdentifierScheme","citation":"https://dataverse.org/schema/citation/","dateOfDeposit":"http://purl.org/dc/terms/dateSubmitted","dcterms":"http://purl.org/dc/terms/","dvcore":"https://dataverse.org/schema/core#","ore":"http://www.openarchives.org/ore/terms/","publication":"http://purl.org/dc/terms/isReferencedBy","publicationCitation":"http://purl.org/dc/terms/bibliographicCitation","publicationIDNumber":"http://purl.org/spar/datacite/ResourceIdentifier","publicationIDType":"http://purl.org/spar/datacite/ResourceIdentifierScheme","publicationURL":"https://schema.org/distribution","schema":"http://schema.org/","subject":"http://purl.org/dc/terms/subject","title":"http://purl.org/dc/terms/title"}}