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Monocular Camera Calibration for Autonomous Driving — a comparative study

2020-04-15Journal article Restricted access
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dc.contributor.authorMartins, Pedro Filipe
dc.contributor.authorCostelha, Hugo
dc.contributor.authorBento, Luís Conde
dc.contributor.authorNeves, Carlos
dc.date.accessioned2020-07-08T13:47:38Z
dc.date.available2020-07-08T13:47:38Z
dc.date.issued2020-04-15
dc.description.abstractAutonomous driving is currently a widely researched topic worldwide. With a large research effort being taken by industrial research units in the automotive sector, it is no longer exclusive to academic research labs. Essential to this ongoing effort towards level-5 vehicle autonomy, are the sensors used for tracking and detection, mainly lasers, radars and cameras. Most of the cameras for automotive application systems use wide-angle or fish-eye lens, which present high distortion levels. Cameras need to be calibrated for correct perception, particularly for capturing geometry features, or for distance-based calculations. This paper describes a case-study concerning monocular camera calibration for a small scale autonomous driving vehicle vision system. It describes the fundamentals on camera calibration and implementation, with results given for different lenses and distortion models. The aim of the paper is not only to provide a detailed and comprehensive review on the application of these calibration methods, but to serve also as a reference document for other researchers and developers starting to use monocular vision in their robotic applications.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationP. F. Martins, H. Costelha, L. C. Bento and C. Neves, "Monocular Camera Calibration for Autonomous Driving — a comparative study," 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Ponta Delgada, Portugal, 2020, pp. 306-311, doi: 10.1109/ICARSC49921.2020.9096104.pt_PT
dc.identifier.doi10.1109/ICARSC49921.2020.9096104pt_PT
dc.identifier.isbn978-1-7281-7078-7
dc.identifier.urihttp://hdl.handle.net/10400.8/5000
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relationINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
dc.relationInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9096104pt_PT
dc.subjectAutonomous Drivingpt_PT
dc.subjectCamera Calibrationpt_PT
dc.subjectRoboticspt_PT
dc.titleMonocular Camera Calibration for Autonomous Driving — a comparative studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleINESC TEC- Institute for Systems and Computer Engineering, Technology and Science
oaire.awardTitleInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50014%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00308%2F2020/PT
oaire.citation.conferencePlacePonta Delgada, Açores, Portugalpt_PT
oaire.citation.endPage311pt_PT
oaire.citation.startPage306pt_PT
oaire.citation.titleICARSC 2020: 20th IEEE International Conference on Autonomous Robot Systems and Competitionspt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameCostelha
person.familyNameConde Bento
person.givenNameHugo
person.givenNameLuis
person.identifier.ciencia-id931E-2249-DBA3
person.identifier.ciencia-idFE12-AAD0-3AB3
person.identifier.orcid0000-0003-0063-8592
person.identifier.orcid0000-0002-9689-3637
person.identifier.ridV-4722-2017
person.identifier.ridF-7888-2013
person.identifier.scopus-author-id24775187600
person.identifier.scopus-author-id14070145000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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