Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/84359
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dc.contributor.authorMei, C.-
dc.contributor.authorSibley, G.-
dc.contributor.authorCummins, M.-
dc.contributor.authorNewman, P.-
dc.contributor.authorReid, I.-
dc.date.issued2009-
dc.identifier.citationProceedings of the British Machine Vision Conference, 7-10 September 2009 / A. Cavallaro, S. Prince and D. Alexander (eds.): pp.54.1-54.11-
dc.identifier.isbn1901725391-
dc.identifier.isbn9781901725391-
dc.identifier.urihttp://hdl.handle.net/2440/84359-
dc.description.abstractContinuous, real-time mapping of an environment using a camera requires a constanttime estimation engine. This rules out optimal global solving such as bundle adjustment. In this article, we investigate the precision that can be achieved with only local estimation of motion and structure provided by a stereo pair. We introduce a simple but novel representation of the environment in terms of a sequence of relative locations. We demonstrate precise local mapping and easy navigation using the relative map, and importantly show that this can be done without requiring a global minimisation after loop closure. We discuss some of the issues that arise from using a relative representation, and evaluate our system on long sequences processed at a constant 30-45 Hz, obtaining precisions down to a few metres over distances of a few kilometres.-
dc.description.statementofresponsibilityChristopher Mei, Gabe Sibley, Mark Cummins, Paul Newman, Ian Reid-
dc.description.urihttp://www.bmva.org/bmvc/2009/index.htm-
dc.language.isoen-
dc.publisherBMVA Press-
dc.rights© 2009 The Authors-
dc.source.urihttp://dx.doi.org/10.5244/c.23.54-
dc.titleA constant time efficient stereo SLAM system-
dc.typeConference paper-
dc.contributor.conferenceBritish Machine Vision Conference (20th : 2009 : London, United Kingdom)-
dc.identifier.doi10.5244/C.23.54-
dc.publisher.placeUnited Kingdom-
pubs.publication-statusPublished-
dc.identifier.orcidReid, I. [0000-0001-7790-6423]-
Appears in Collections:Aurora harvest 4
Computer Science publications

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