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dc.contributor.authorWhelan, Thomas
dc.contributor.authorJohannsson, Hordur
dc.contributor.authorKaess, Michael
dc.contributor.authorMcDonald, John
dc.contributor.authorLeonard, John Joseph
dc.date.accessioned2015-06-29T15:43:45Z
dc.date.available2015-06-29T15:43:45Z
dc.date.issued2013-05
dc.identifier.isbn978-1-4673-5643-5
dc.identifier.isbn978-1-4673-5641-1
dc.identifier.issn1050-4729
dc.identifier.urihttp://hdl.handle.net/1721.1/97552
dc.description.abstractThis paper describes extensions to the Kintinuous [1] algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused realtime surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-10-1-0936)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-11-1-0688)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-12-10020)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICRA.2013.6631400en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceOther repositoryen_US
dc.titleRobust real-time visual odometry for dense RGB-D mappingen_US
dc.typeArticleen_US
dc.identifier.citationWhelan, Thomas, Hordur Johannsson, Michael Kaess, John J. Leonard, and John McDonald. “Robust Real-Time Visual Odometry for Dense RGB-D Mapping.” 2013 IEEE International Conference on Robotics and Automation (May 2013).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.mitauthorJohannsson, Horduren_US
dc.contributor.mitauthorKaess, Michaelen_US
dc.contributor.mitauthorLeonard, John Josephen_US
dc.relation.journalProceedings of the 2013 IEEE International Conference on Robotics and Automationen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsWhelan, Thomas; Johannsson, Hordur; Kaess, Michael; Leonard, John J.; McDonald, Johnen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8863-6550
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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