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3D Object Reconstruction with Heterogeneous Sensor Data

hal.structure.identifierUniversity of North Carolina [Chapel Hill] [UNC]
hal.structure.identifierEidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] [ETH Zürich]
dc.contributor.authorGUAN, Li
hal.structure.identifierVisualization and manipulation of complex data on wireless mobile devices [IPARLA ]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorFRANCO, Jean-Sébastien
hal.structure.identifierUniversity of North Carolina [Chapel Hill] [UNC]
hal.structure.identifierEidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] [ETH Zürich]
dc.contributor.authorPOLLEFEYS, Marc
dc.date.accessioned2024-04-15T09:52:55Z
dc.date.available2024-04-15T09:52:55Z
dc.date.issued2008
dc.date.conference2008-06-18
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198562
dc.description.abstractEnIn this paper, we reconstruct 3D objects with a heterogeneous sensor network of Range Imaging(RIM) sensors and high-res camcorders. With this setup, we first carry out simple but effective depth calibration for the RIM cameras. We then combine the camcorder silhouette cues and RIM camera depth information, for the reconstruction. Our main contribution is the proposal of a sensor fusion framework so that the computation is general, simple and scalable. Although we only discuss the camcorders and RIM cameras in this paper, the proposed framework can be applied to any type of vision sensors. It uses a space occupancy grid as a probabilistic 3D representation of scene contents. After defining sensing models for each type of sensors, the reconstruction is simply a Bayesian inference problem, and can be solved robustly. The experiments show that the recover full 3D closed shapes substantially improved the quality of the noisy RIM sensor measurement.
dc.description.sponsorshipData trAnsfert for Large Interactive Applications - ANR-06-MDCA-0003
dc.language.isoen
dc.title.en3D Object Reconstruction with Heterogeneous Sensor Data
dc.typeCommunication dans un congrès
dc.subject.halInformatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleInternational Symposium on 3D Data Processing, Visualization and Transmission
bordeaux.countryUS
bordeaux.conference.cityAtlanta
bordeaux.peerReviewedoui
hal.identifierinria-00349099
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00349099v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2008&rft.au=GUAN,%20Li&FRANCO,%20Jean-S%C3%A9bastien&POLLEFEYS,%20Marc&rft.genre=unknown


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