Visibility Estimation and Joint Inpainting of Lidar Depth Maps
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
hal.structure.identifier | Méthodes d'Analyses pour le Traitement d'Images et la Stéréorestitution [MATIS] | |
dc.contributor.author | BEVILACQUA, Marco | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
dc.contributor.author | AUJOL, Jean-François | |
hal.structure.identifier | Méthodes d'Analyses pour le Traitement d'Images et la Stéréorestitution [MATIS] | |
dc.contributor.author | BRÉDIF, Mathieu | |
hal.structure.identifier | Laboratoire Bordelais de Recherche en Informatique [LaBRI] | |
dc.contributor.author | BUGEAU, Aurélie | |
dc.date.accessioned | 2024-04-04T03:14:45Z | |
dc.date.available | 2024-04-04T03:14:45Z | |
dc.date.conference | 2016-09-25 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/194088 | |
dc.description.abstractEn | This paper presents a novel variational image inpainting method to solve the problem of generating, from 3-D lidar measures, a dense depth map coherent with a given color image, tackling visibility issues. When projecting the lidar point cloud onto the image plane, we generally obtain a sparse depth map, due to undersampling. Moreover , lidar and image sensor positions generally differ during acquisition , such that depth values referring to objects that are hidden from the image view point might appear with a naive projection. The proposed algorithm estimates the complete depth map, while simultaneously detecting and excluding those hidden points. It consists in a primal-dual optimization method, where a coupled total variation regularization term is included to match the depth and image gradients and a visibility indicator handles the selection of visible points. Tests with real data prove the effectiveness of the proposed strategy. | |
dc.language.iso | en | |
dc.subject.en | Inpainting | |
dc.subject.en | Total Variation | |
dc.subject.en | Depth Maps | |
dc.subject.en | Lidar | |
dc.subject.en | Point Cloud | |
dc.subject.en | Visibility | |
dc.title.en | Visibility Estimation and Joint Inpainting of Lidar Depth Maps | |
dc.type | Communication dans un congrès | |
dc.subject.hal | Informatique [cs]/Traitement des images | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.conference.title | IEEE International Conference on Image Processing (ICIP) | |
bordeaux.country | US | |
bordeaux.conference.city | Phoenix, AZ | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-01316719 | |
hal.version | 1 | |
hal.invited | non | |
hal.proceedings | oui | |
hal.conference.end | 2016-09-28 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-01316719v1 | |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=BEVILACQUA,%20Marco&AUJOL,%20Jean-Fran%C3%A7ois&BR%C3%89DIF,%20Mathieu&BUGEAU,%20Aur%C3%A9lie&rft.genre=unknown |
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