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dc.contributor.authorJeon, Seung-Hyuk
dc.contributor.authorChung, Yun-koo
dc.contributor.authorYoon, Ho-sub
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-11-08T13:18:12Z
dc.date.available2017-11-08T13:18:12Z
dc.date.issued2014
dc.identifier.citationWSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 369-374.en
dc.identifier.isbn978-80-86943-71-8
dc.identifier.uriwscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26436
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2014: communication papers proceedingsen
dc.rights@ Václav Skala - UNION Agencycs
dc.subjectrozpoznání chodníkucs
dc.subjectdetekce řádkůcs
dc.subjectodhad mrtvých bodůcs
dc.subjectobrazy přírodní scénycs
dc.titleEstimating the vanishing point of a sidewalken
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn this paper, we propose an algorithm estimating the vanishing point (VP) of a sidewalk in a man-made environment from a single image. For finding the VP, the lines in an image are efficiently exploited as a clue because the projections of parallel lines in an image intersect at a VP. However, there are too many noises disturbing line detection in natural scene images, for example trees, pedestrian and shadows. Thus, we suggest a noise reduction technique called orientation consistency pass filtering (OCPF) for improving line detection performance. An edge orientation at the window center of OCPF is compared to its neighbor edge orientations for calculating orientation difference. The center pixel is removed if the difference of edge orientations greater than a threshold, and preserved otherwise. In addition, we suggest a novel vanishing point detection method using edge orientation voting (EOV), which predict VP position accurately. The lines filtered by OCPF can generate the VP candidates using bottom-up extended lines. The VP candidates receive supports from all edges below the currently inspected VP candidate. The most supported VP candidate is selected as dominant VP. This proposed method was implemented and tested on 600 sidewalk image database that has 640x320 resolutions. 74.3 % of the test sidewalk images are in range from 0 pixels to 20 pixels from manually marked VP.en
dc.subject.translatedsidewalk recognitionen
dc.subject.translatedline detectionen
dc.subject.translatedvanishing point estimationen
dc.subject.translatednatural scene imagesen
dc.type.statusPeer-revieweden
Appears in Collections:WSCG 2014: Communication Papers Proceedings

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