Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81252
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorTang, SJ-
dc.creatorZhu, Q-
dc.creatorChen, W-
dc.creatorWang, WX-
dc.creatorLi, Y-
dc.creatorDarwish, W-
dc.creatorLi, WB-
dc.date.accessioned2019-08-23T08:29:55Z-
dc.date.available2019-08-23T08:29:55Z-
dc.identifier.issn2194-9042-
dc.identifier.urihttp://hdl.handle.net/10397/81252-
dc.description4th ISPRS Geospatial Week 2019, Netherlands, 10-14 June 2019en_US
dc.language.isoenen_US
dc.publisherCopernicus Publicationsen_US
dc.rights© Authors 2019. CC BY 4.0 License. This work is distributed under the Creative Commons Attribution 4.0 License.en_US
dc.rightsThe following publication Tang, S. J., Zhu, Q., Chen, W., Wang, W. X., Li, Y., Darwish, W., and Li, W. B.: A FREQUENCY-DRIFT COMPENSATED CLOSED-FORM SOLUTION FOR STEREO RGB-D MAPPING, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 293-297 is available at https://doi.org/10.5194/isprs-annals-IV-2-W5-293-2019, 2019en_US
dc.subjectCamera trackingen_US
dc.subjectIndoor mappingen_US
dc.subjectPoint clouden_US
dc.subjectStereo cameraen_US
dc.titleA frequency-drift compensated closed-form solution for stereo RGB-D mappingen_US
dc.typeConference Paperen_US
dc.identifier.spage293-
dc.identifier.epage297-
dc.identifier.volume4-
dc.identifier.issue2/W5-
dc.identifier.doi10.5194/isprs-annals-IV-2-W5-293-2019-
dcterms.abstractIn this work, we present a frequency-drift compensated (Fd-C) closed-form solution for stereo RGB-D SLAM. The intrinsic parameters for each sensor are first obtained with a standard camera calibration process and the extrinsic orientation parameters achieved through a coarse-to-fine scheme that solves the initial exterior orientation parameters (EoPs) from control markers and further refines the initial value by an iterative closest point (ICP) variant minimizing the distance between the RGB-D point clouds and the referenced laser point clouds. With the assumption of fix transformation between the frames with the same timestamp, we define one sensor as reference sensor and the other sensor as slave sensor and the slave frames can be mapped to the timeline of the references sensor. Rather than endow the camera pose of the nearest frame to the slave frames, we derive the accurate camera pose for slave frames in a spatially variant way. Therefore, the pose relations between the slave frame and the adjacent reference frame can be derived, which provided opportunity to use the more accuracy observations from multiple frames for better tracking and global optimization. We present the mathematical analysis of the iterative optimizations for pose tracking in multi-RGB-D camera cases. Finally, the experiments in complex indoor scenarios demonstrate the efficiency of the proposed multiple RGB-D slam algorithm.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS annals of the photogrammetry, remote sensing and spatial information sciences, 2019, v. 4, no. 2/W5, p. 293-297-
dcterms.isPartOfISPRS annals of the photogrammetry, remote sensing and spatial information sciences-
dcterms.issued2019-
dc.identifier.scopus2-s2.0-85067500714-
dc.relation.conferenceISPRS Geospatial Week-
dc.identifier.eissn2194-9050-
dc.description.validate201908 bcma-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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