Enabling Visual Recognition at Radio Frequency
<|reference_start|>Enabling Visual Recognition at Radio Frequency: This paper introduces PanoRadar, a novel RF imaging system that brings RF resolution close to that of LiDAR, while providing resilience against conditions challenging for optical signals. Our LiDAR-comparable 3D imaging results enable, for the first time, a variety of visual recognition tasks at radio frequency, including surface normal estimation, semantic segmentation, and object detection. PanoRadar utilizes a rotating single-chip mmWave radar, along with a combination of novel signal processing and machine learning algorithms, to create high-resolution 3D images of the surroundings. Our system accurately estimates robot motion, allowing for coherent imaging through a dense grid of synthetic antennas. It also exploits the high azimuth resolution to enhance elevation resolution using learning-based methods. Furthermore, PanoRadar tackles 3D learning via 2D convolutions and addresses challenges due to the unique characteristics of RF signals. Our results demonstrate PanoRadar's robust performance across 12 buildings.<|reference_end|>
@article{lai2024enabling,
    title={Enabling Visual Recognition at Radio Frequency},
    author={Haowen Lai, Gaoxiang Luo, Yifei Liu, Mingmin Zhao},
    journal={arXiv preprint arXiv:2405.19516},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.19516},
    primaryClass={eess.SP cs.CV cs.LG cs.RO}
}