ReFeree: Radar-based efficient global descriptor using a Feature and Free space
for Place Recognition

Byunghee Choi*, Hogyun Kim* and Younggun Cho
(* means equally to this work)

Radar is highlighted for robust sensing capabilities in adverse weather conditions (e.g. dense fog, heavy rain, or snowfall).  In addition, Radar can cover wide areas and penetrate small particles. Despite these advantages, Radar-based place recognition remains in the early stages compared to other sensors due to its unique characteristics such as low resolution, and significant noise. In this paper, we propose a Radar-based place recognition utilizing a descriptor called ReFeree using a feature and free space. Unlike traditional methods, we overwhelmingly summarize the Radar image (i.e. 361.5KB →  464B). Despite being lightweight, it contains semi-metric information and is also outstanding from the perspective of place recognition performance. For concrete validation, we test a single session from the MulRan dataset and a multi-session from the Oxford Offroad Radar, Oxford Radar RobotCar, and the Boreas dataset.

@article{choi2024referee,

  title={ReFeree: Radar-based efficient global descriptor using a Feature and Free space for Place Recognition},

  author={Choi, Byunghee and Kim, Hogyun and Cho, Younggun},

  journal={arXiv preprint arXiv:2403.14176},

  year={2024}

}