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Range-Image: Incorporating sensor topology for LiDAR point cloud processing

hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorBIASUTTI, Pierre
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorAUJOL, Jean-François
hal.structure.identifierMéthodes d'Analyses pour le Traitement d'Images et la Stéréorestitution [MATIS]
dc.contributor.authorBRÉDIF, Mathieu
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBUGEAU, Aurélie
dc.date.accessioned2024-04-04T03:06:23Z
dc.date.available2024-04-04T03:06:23Z
dc.date.issued2018-06
dc.identifier.issn0099-1112
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193330
dc.description.abstractEnThis paper proposes a novel methodology for LiDAR point cloud processing that takes advantage of the implicit topology of various LiDAR sensors to derive 2D images from the point cloud while bringing spatial structure to each point. The interest of such a methodology is then proved by addressing the problems of segmentation and disocclusion of mobile objects in 3D LiDAR scenes acquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle those problems directly in the 3D space. This work promotes an alternative approach by using this 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. Using the image derived from the sensor data by exploiting the sensor topology, a semi-automatic segmentation procedure based on depth histograms is presented. Then, a variational image inpainting technique is introduced to reconstruct the areas that are occluded by objects. Experiments and validation on real data prove the effectiveness of this methodology both in terms of accuracy and speed.
dc.language.isoen
dc.publisherAsprs American Society for Photogrammetry and
dc.title.enRange-Image: Incorporating sensor topology for LiDAR point cloud processing
dc.typeArticle de revue
dc.identifier.doi10.14358/PERS.84.6.367
dc.subject.halInformatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
bordeaux.journalPhotogrammetric engineering and remote sensing
bordeaux.page367--375
bordeaux.volume84
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue6
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01756975
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01756975v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Photogrammetric%20engineering%20and%20remote%20sensing&rft.date=2018-06&rft.volume=84&rft.issue=6&rft.spage=367--375&rft.epage=367--375&rft.eissn=0099-1112&rft.issn=0099-1112&rft.au=BIASUTTI,%20Pierre&AUJOL,%20Jean-Fran%C3%A7ois&BR%C3%89DIF,%20Mathieu&BUGEAU,%20Aur%C3%A9lie&rft.genre=article


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