dc.contributor.author | Whelan, Thomas | |
dc.contributor.author | Johannsson, Hordur | |
dc.contributor.author | Kaess, Michael | |
dc.contributor.author | McDonald, John | |
dc.contributor.author | Leonard, John Joseph | |
dc.date.accessioned | 2015-06-29T15:43:45Z | |
dc.date.available | 2015-06-29T15:43:45Z | |
dc.date.issued | 2013-05 | |
dc.identifier.isbn | 978-1-4673-5643-5 | |
dc.identifier.isbn | 978-1-4673-5641-1 | |
dc.identifier.issn | 1050-4729 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/97552 | |
dc.description.abstract | This 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.sponsorship | United States. Office of Naval Research (Grant N00014-10-1-0936) | en_US |
dc.description.sponsorship | United States. Office of Naval Research (Grant N00014-11-1-0688) | en_US |
dc.description.sponsorship | United States. Office of Naval Research (Grant N00014-12-10020) | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/ICRA.2013.6631400 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | Other repository | en_US |
dc.title | Robust real-time visual odometry for dense RGB-D mapping | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Whelan, 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.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
dc.contributor.mitauthor | Johannsson, Hordur | en_US |
dc.contributor.mitauthor | Kaess, Michael | en_US |
dc.contributor.mitauthor | Leonard, John Joseph | en_US |
dc.relation.journal | Proceedings of the 2013 IEEE International Conference on Robotics and Automation | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dspace.orderedauthors | Whelan, Thomas; Johannsson, Hordur; Kaess, Michael; Leonard, John J.; McDonald, John | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-8863-6550 | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |