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Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sangil | - |
dc.contributor.author | Son, Clark Youngdong | - |
dc.contributor.author | Kim, H. Jin | - |
dc.date.accessioned | 2022-11-11T08:07:23Z | - |
dc.date.available | 2022-11-11T08:07:23Z | - |
dc.date.created | 2022-10-19 | - |
dc.date.issued | 2019-11 | - |
dc.identifier.citation | 2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), pp.6891-6898 | - |
dc.identifier.issn | 2153-0858 | - |
dc.identifier.uri | https://hdl.handle.net/10371/187063 | - |
dc.description.abstract | In the paper, we propose a robust real-time visual odometry in dynamic environments via rigid-motion model updated by scene flow. The proposed algorithm consists of spatial motion segmentation and temporal motion tracking. The spatial segmentation first generates several motion hypotheses by using a grid-based scene flow and clusters the extracted motion hypotheses, separating objects that move independently of one another. Further, we use a dual-mode motion model to consistently distinguish between the static and dynamic parts in the temporal motion tracking stage. Finally, the proposed algorithm estimates the pose of a camera by taking advantage of the region classified as static parts. In order to evaluate the performance of visual odometry under the existence of dynamic rigid objects, we use self-collected dataset containing RGB-D images and motion capture data for ground-truth. We compare our algorithm with state-of-the-art visual odometry algorithms. The validation results suggest that the proposed algorithm can estimate the pose of a camera robustly and accurately in dynamic environments. | - |
dc.language | 영어 | - |
dc.publisher | IEEE | - |
dc.title | Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/IROS40897.2019.8968208 | - |
dc.citation.journaltitle | 2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | - |
dc.identifier.wosid | 000544658405032 | - |
dc.identifier.scopusid | 2-s2.0-85081162128 | - |
dc.citation.endpage | 6898 | - |
dc.citation.startpage | 6891 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Kim, H. Jin | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
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