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hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBIASUTTI, Pierre
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorAUJOL, Jean-François
hal.structure.identifierInstitut National de l'Information Géographique et Forestière [IGN] [IGN]
dc.contributor.authorBRÉDIF, Mathieu
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBUGEAU, Aurélie
dc.date.accessioned2024-04-04T03:10:10Z
dc.date.available2024-04-04T03:10:10Z
dc.date.conference2017-06-06
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193667
dc.description.abstractEnThis paper proposes a novel framework for the disocclusion of mobile objects in 3D LiDAR scenes aquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle this problem directly in the 3D space. This work promotes an alternative approach by using a 2D range image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. First, the point cloud is turned into a 2D range image by exploiting the sensor's topology. Using the range image, a semi-automatic segmentation procedure based on depth histograms is performed in order to select the occluding object to be removed. A variational image inpainting technique is then used to reconstruct the area occluded by that object. Finally, the range image is unprojected as a 3D point cloud. Experiments on real data prove the effectiveness of this procedure both in terms of accuracy and speed.
dc.language.isoen
dc.subject.envariational
dc.subject.enLiDAR
dc.subject.enpoint cloud
dc.subject.enInpainting
dc.subject.endisocclusion
dc.subject.ensegmentation
dc.title.enDisocclusion of 3D LiDAR point clouds using range images
dc.typeCommunication dans un congrès
dc.identifier.doi10.5194/isprs-annals-IV-1-W1-75-2017
dc.subject.halInformatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
bordeaux.page75 - 82
bordeaux.volumeIV-1/W1
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleCity Models, Roads and Traffic workshop (CMRT)
bordeaux.countryDE
bordeaux.conference.cityHannover
bordeaux.peerReviewedoui
hal.identifierhal-01522366
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2017-06-09
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01522366v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.volume=IV-1/W1&rft.spage=75%20-%2082&rft.epage=75%20-%2082&rft.au=BIASUTTI,%20Pierre&AUJOL,%20Jean-Fran%C3%A7ois&BR%C3%89DIF,%20Mathieu&BUGEAU,%20Aur%C3%A9lie&rft.genre=unknown


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