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Please use this identifier to cite or link to this item: https://doi.org/10.1109/IVS.2013.6629636
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dc.titleRoad detection and mapping using 3D rolling window
dc.contributor.authorQin, B.
dc.contributor.authorChong, Z.J.
dc.contributor.authorBandyopadhyay, T.
dc.contributor.authorAng, M.H.
dc.contributor.authorFrazzoli, E.
dc.contributor.authorRus, D.
dc.date.accessioned2014-10-07T09:15:32Z
dc.date.available2014-10-07T09:15:32Z
dc.date.issued2013
dc.identifier.citationQin, B.,Chong, Z.J.,Bandyopadhyay, T.,Ang, M.H.,Frazzoli, E.,Rus, D. (2013). Road detection and mapping using 3D rolling window. IEEE Intelligent Vehicles Symposium, Proceedings : 1239-1246. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/IVS.2013.6629636" target="_blank">https://doi.org/10.1109/IVS.2013.6629636</a>
dc.identifier.isbn9781467327558
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/86072
dc.description.abstractThis paper presents a method of road detection and mapping using accumulated 3D data from 2D scans. The idea of 3D rolling window is introduced, and its probabilisitc characteristics are studied. A cascaded road detection process is developed with region-growing and classification methods. A probabilistic framework is utlized for road mapping purposes with the detection results. The performance of detection and mapping algorithm is evaluated through experiments. © 2013 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IVS.2013.6629636
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1109/IVS.2013.6629636
dc.description.sourcetitleIEEE Intelligent Vehicles Symposium, Proceedings
dc.description.page1239-1246
dc.identifier.isiutNOT_IN_WOS
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