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주경돈

Joo, Kyungdon
Robotics and Visual Intelligence Lab.
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dc.citation.endPage 404 -
dc.citation.number 2 -
dc.citation.startPage 384 -
dc.citation.title INTERNATIONAL JOURNAL OF COMPUTER VISION -
dc.citation.volume 130 -
dc.contributor.author Rameau, Francois -
dc.contributor.author Bailo, Oleksandr -
dc.contributor.author Park, Jinsun -
dc.contributor.author Joo, Kyungdon -
dc.contributor.author Kweon, In So -
dc.date.accessioned 2023-12-21T14:42:51Z -
dc.date.available 2023-12-21T14:42:51Z -
dc.date.created 2022-01-07 -
dc.date.issued 2022-01 -
dc.description.abstract In this paper, we propose a multi-vehicle localization approach relying exclusively on cameras installed on connected cars (e.g. vehicles with Internet access). The proposed method is designed to perform in real-time while requiring a low bandwidth connection as a result of an efficient distributed architecture. Hence, our approach is compatible with both LTE Internet connection and local Wi-Fi networks. To reach this goal, the vehicles share small portions of their respective 3D maps to estimate their relative positions. The global consistency between multiple vehicles is enforced via a novel graph-based strategy. The efficiency of our system is highlighted through a series of real experiments involving multiple vehicles. Moreover, the usefulness of our technique is emphasized by an innovative and unique multi-car see-through system resolving the inherent limitations of the previous approaches. A video demonstration is available via: https://youtu.be/GD7Z95bWP6k. -
dc.identifier.bibliographicCitation INTERNATIONAL JOURNAL OF COMPUTER VISION, v.130, no.2, pp.384 - 404 -
dc.identifier.doi 10.1007/s11263-021-01558-5 -
dc.identifier.issn 0920-5691 -
dc.identifier.scopusid 2-s2.0-85122254088 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/56563 -
dc.identifier.url https://link.springer.com/article/10.1007%2Fs11263-021-01558-5 -
dc.identifier.wosid 000738511800004 -
dc.language 영어 -
dc.publisher SPRINGER -
dc.title Real-Time Multi-Car Localization and See-Through System -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Computer Science, Artificial Intelligence -
dc.relation.journalResearchArea Computer Science -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Simultaneous localization and mapping -
dc.subject.keywordAuthor Collaborative SLAM -
dc.subject.keywordAuthor Connected vehicles -
dc.subject.keywordAuthor See-through -
dc.subject.keywordPlus SLAM -
dc.subject.keywordPlus ACCURACY -

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