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dc.contributor.authorKrämer, Marc Steven
dc.contributor.authorKuhnert, Lars
dc.contributor.authorKuhnert, Klaus-Dieter
dc.contributor.editorSkala, Václav
dc.date.accessioned2019-05-10T09:29:47Z-
dc.date.available2019-05-10T09:29:47Z-
dc.date.issued2018
dc.identifier.citationWSCG 2018: full papers proceedings: 26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS Association, p. 78-87.en
dc.identifier.isbn978-80-86943-40-4
dc.identifier.issn2464–4617 (print)
dc.identifier.issn2464–4625 (CD-ROM)
dc.identifier.uriwscg.zcu.cz/WSCG2018/!!_CSRN-2801.pdf
dc.identifier.urihttp://hdl.handle.net/11025/34627
dc.description.abstractIn this paper, we propose a fast and real-time capable system for visual off-road path detection. We equipped our robot AMOR with a single monocular camera and explored unstructured environments like woods. In these areas, it is almost harder to identify and classify drivable and non-drivable parts in an image. In urban regions, roads can be detected by lane markers or delimitations whereas the boundaries of a forest path blend into the environment almost seamlessly. In our work, we developed a software system that is based on mostly simple and low computationally intensive algorithms. We developed and tested the functions with a large dataset of camera images and also generated a manually Ground Truth for the evaluation.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencyen
dc.subjectdetekce silniccs
dc.subjectterénní autonomní navigacecs
dc.subjectsegmentace obrazucs
dc.subjectklasifikace terénucs
dc.subjectmobilní robotycs
dc.titleReal-time visual off-road path detectionen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedroad detectionen
dc.subject.translatedoff-road autonomous navigationen
dc.subject.translatedimage segmentationen
dc.subject.translatedterrain classificationen
dc.subject.translatedmobile robotsen
dc.identifier.doihttps://doi.org/10.24132/CSRN.2018.2801.9
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2018: Full Papers Proceedings

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