Online 3D reconstruction and 6-DoF pose estimation for RGB-D sensors
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lim, Hyon | - |
dc.contributor.author | Lim, Jongwoo | - |
dc.contributor.author | Jin, Kim Hyoun | - |
dc.date.accessioned | 2022-07-15T21:05:10Z | - |
dc.date.available | 2022-07-15T21:05:10Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2015-09 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/156410 | - |
dc.description.abstract | In this paper, we propose an approach to Simultaneous Localization and Mapping (SLAM) for RGB-D sensors. Our system computes 6-DoF pose and sparse feature map of the environment. We propose a novel keyframe selection scheme based on the Fisher information, and new loop closing method that utilizes feature-to-landmark correspondences inspired by image-based localization. As a result, the system effectively mitigates drift that is frequently observed in visual odometry system. Our approach gives lowest relative pose error amongst any other approaches tested on public benchmark dataset. A set of 3D reconstruction results on publicly available RGB-D videos are presented. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Springer Verlag | - |
dc.title | Online 3D reconstruction and 6-DoF pose estimation for RGB-D sensors | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lim, Jongwoo | - |
dc.identifier.doi | 10.1007/978-3-319-16178-5_16 | - |
dc.identifier.scopusid | 2-s2.0-84925295905 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.8925, pp.238 - 254 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 8925 | - |
dc.citation.startPage | 238 | - |
dc.citation.endPage | 254 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Fisher information matrix | - |
dc.subject.keywordPlus | Mapping | - |
dc.subject.keywordPlus | Robotics | - |
dc.subject.keywordPlus | 3D reconstruction | - |
dc.subject.keywordPlus | 6-dof pose estimations | - |
dc.subject.keywordPlus | Benchmark datasets | - |
dc.subject.keywordPlus | Fisher information | - |
dc.subject.keywordPlus | Image-based localizations | - |
dc.subject.keywordPlus | Key frame selection | - |
dc.subject.keywordPlus | RGB-D SLAM | - |
dc.subject.keywordPlus | Simultaneous localization and mapping | - |
dc.subject.keywordPlus | Computer vision | - |
dc.subject.keywordAuthor | RGB-D SLAM | - |
dc.subject.keywordAuthor | Simultaneous localization and mapping | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-319-16178-5_16 | - |
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