Meaningful maps with object-oriented semantic mapping

dc.contributor.authorSünderhauf, N.
dc.contributor.authorPham, T.
dc.contributor.authorLatif, Y.
dc.contributor.authorMilford, M.
dc.contributor.authorReid, I.
dc.contributor.conference2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (24 Sep 2017 - 28 Sep 2017 : Vancouver, Canada)
dc.contributor.editorBicchi, A.
dc.contributor.editorOkamura, A.
dc.date.issued2017
dc.description.abstractFor intelligent robots to interact in meaningful ways with their environment, they must understand both the geometric and semantic properties of the scene surrounding them. The majority of research to date has addressed these mapping challenges separately, focusing on either geometric or semantic mapping. In this paper we address the problem of building environmental maps that include both semantically meaningful, object-level entities and point- or mesh-based geometrical representations. We simultaneously build geometric point cloud models of previously unseen instances of known object classes and create a map that contains these object models as central entities. Our system leverages sparse, feature-based RGB-D SLAM, image-based deep-learning object detection and 3D unsupervised segmentation.
dc.description.statementofresponsibilityNiko Sünderhauf, Trung T. Pham, Yasir Latif, Michael Milford, Ian Reid
dc.identifier.citationProceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017 / Bicchi, A., Okamura, A. (ed./s), vol.2017-September, pp.5079-5085
dc.identifier.doi10.1109/IROS.2017.8206392
dc.identifier.isbn9781538626825
dc.identifier.issn2153-0858
dc.identifier.issn2153-0866
dc.identifier.orcidLatif, Y. [0000-0002-2529-5322]
dc.identifier.urihttp://hdl.handle.net/2440/111586
dc.language.isoen
dc.publisherIEEE
dc.relation.granthttp://purl.org/au-research/grants/arc/FT140101229
dc.relation.ispartofseriesIEEE International Conference on Intelligent Robots and Systems
dc.rights©2017 IEEE
dc.source.urihttps://doi.org/10.1109/iros.2017.8206392
dc.titleMeaningful maps with object-oriented semantic mapping
dc.typeConference paper
pubs.publication-statusPublished

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