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dc.contributor.authorKang, Dong-Joong-
dc.contributor.authorLim, Sung-Jo-
dc.contributor.authorHa, Jong-Eun-
dc.contributor.authorJeong, Mun-Ho-
dc.date.accessioned2024-01-20T21:33:31Z-
dc.date.available2024-01-20T21:33:31Z-
dc.date.created2021-09-03-
dc.date.issued2009-04-01-
dc.identifier.issn0167-8655-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/132577-
dc.description.abstractThis paper presents a method to recognize plane regions for unobstructed motion of mobile robots. When an autonomous agency, using a stereo camera or a laser scanning sensor, is in an unknown 3D environment, the mobile agency must detect the plane regions so that it can independently decide its direction of movement in order to perform assigned tasks. In this paper, a fast method of plane detection is proposed, wherein the normal vector of a triangle is inscribed in a small circular region such that the normal vector passes through the circumcenter area of the triangle. To reduce the effects of noise and outliers, the triangle is rotationally sampled with respect to the center position of the circular region, and a series of inscribed triangles having different normal vectors is generated. The direction vectors of these generated triangles are normalized and the median direction of the normal vectors is then used to test the planarity of the circular region. A pose finding procedure is introduced from range data of a surface to decide the scale and rotation angle of the circular region superimposed on range image data. The method of plane detection is very fast as computation of local information about the plane typically requires sub-ms duration, and the performance of the algorithm for real range data obtained from a stereo camera system has been verified. Crown Copyright (c) 2008 Published by Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER-
dc.subjectSEGMENTATION-
dc.titleA detection cell using multiple points of a rotating triangle to find local planar regions from stereo depth data-
dc.typeArticle-
dc.identifier.doi10.1016/j.patrec.2008.11.011-
dc.description.journalClass1-
dc.identifier.bibliographicCitationPATTERN RECOGNITION LETTERS, v.30, no.5, pp.486 - 493-
dc.citation.titlePATTERN RECOGNITION LETTERS-
dc.citation.volume30-
dc.citation.number5-
dc.citation.startPage486-
dc.citation.endPage493-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000264471600003-
dc.identifier.scopusid2-s2.0-60249084248-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalResearchAreaComputer Science-
dc.type.docTypeArticle-
dc.subject.keywordPlusSEGMENTATION-
dc.subject.keywordAuthorPlane recognition-
dc.subject.keywordAuthorObstacle detection-
dc.subject.keywordAuthorRange data-
dc.subject.keywordAuthorStereo sensor-
dc.subject.keywordAuthorMobile robot-
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KIST Article > 2009
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