Effects of Environment Model Parametrization on Photogrametry Reconstruction

dc.contributor.authorKlecka, Jan
dc.coverage.issue1cs
dc.coverage.volume24cs
dc.date.accessioned2019-06-26T10:18:37Z
dc.date.available2019-06-26T10:18:37Z
dc.date.issued2018-06-01cs
dc.description.abstractThis paper is aimed at a description of effects which have assumptions of specific environment structure on quality of recurrently conducted photogrammetry reconstruction. The theoretical part covers the description of three different assumptions of environment structure and mathematical derivation of two suitable recurrent estimators: one based on Extended Kalman filter and the second one based on Maximum likelihood method. The experimental part is introducing simple virtual environment which is observed by linear camera model and then reconstructed using predefined algorithms and assumptions.en
dc.formattextcs
dc.format.extent151-158cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2018 vol. 24, č. 1, s. 151-158. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2018.1.151en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179237
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/36cs
dc.rights.accessopenAccessen
dc.subjectPhotogrammetryen
dc.subject3D reconstructionen
dc.subjectMultiple view reconstructionen
dc.subjectrecurrent estimationen
dc.subjectmaximum likelihooden
dc.subjectExtended Kalman filteren
dc.titleEffects of Environment Model Parametrization on Photogrametry Reconstructionen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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