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UNIST 인공지능대학원의 대학원 및 연구성과를 확인하실 수 있습니다.

Real-Time Multi-Car Localization and See-Through System (IJCV 22), Prof. Joo, Kyungdon

  • 2022
  • 01.01 - 12.31

Real-Time Multi-Car Localization and See-Through System


Rameau, Francois / Bailo, Oleksandr / Park, Jinsun / Joo, Kyungdon / Kweon, In So

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.

site link: https://dl.acm.org/doi/abs/10.1007/s11263-021-01558-5