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주경돈

Joo, Kyungdon
Robotics and Visual Intelligence Lab.
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Real-Time Multi-Car Localization and See-Through System

Author(s)
Rameau, FrancoisBailo, OleksandrPark, JinsunJoo, KyungdonKweon, In So
Issued Date
2022-01
DOI
10.1007/s11263-021-01558-5
URI
https://scholarworks.unist.ac.kr/handle/201301/56563
Fulltext
https://link.springer.com/article/10.1007%2Fs11263-021-01558-5
Citation
INTERNATIONAL JOURNAL OF COMPUTER VISION, v.130, no.2, pp.384 - 404
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.
Publisher
SPRINGER
ISSN
0920-5691
Keyword (Author)
Simultaneous localization and mappingCollaborative SLAMConnected vehiclesSee-through
Keyword
SLAMACCURACY

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