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dc.contributor.authorNi, Kai
dc.contributor.authorDellaert, Frank
dc.contributor.authorKaess, Michael
dc.date.accessioned2010-10-19T16:01:00Z
dc.date.available2010-10-19T16:01:00Z
dc.date.issued2009-07
dc.identifier.isbn978-1-4244-2788-8
dc.identifier.issn1050-4729
dc.identifier.urihttp://hdl.handle.net/1721.1/59404
dc.description.abstractSeparating sparse flow provides fast and robust stereo visual odometry that deals with nearly degenerate situations that often arise in practical applications.We make use of the fact that in outdoor situations different constraints are provided by close and far structure, where the notion of close depends on the vehicle speed. The motion of distant features determines the rotational component that we recover with a robust two-point algorithm. Once the rotation is known, we recover the translational component from close features using a robust one-point algorithm. The overall algorithm is faster than estimating the motion in one step by a standard RANSAC-based three-point algorithm. And in contrast to other visual odometry work, we avoid the problem of nearly degenerate data, under which RANSAC is known to return inconsistent results. We confirm our claims on data from an outdoor robot equipped with a stereo rig.en_US
dc.description.sponsorshipUnited States. Defense Advanced Research Projects Agency (grant FA8650-04-C-7131)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ROBOT.2009.5152333en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceIEEEen_US
dc.titleFlow separation for fast and robust stereo odometryen_US
dc.typeArticleen_US
dc.identifier.citationKaess, M., Kai Ni, and F. Dellaert. “Flow separation for fast and robust stereo odometry.” Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. 2009. 3539-3544. © 2009 IEEEen_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.approverKaess, Michael
dc.contributor.mitauthorKaess, Michael
dc.relation.journalIEEE International Conference on Robotics and Automation, 2009. ICRA '09.en_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsKaess, M.; Kai Ni, M.; Dellaert, F.en
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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