Non-line-of-sight (NLOS) imaging is an emerging technique for detecting objects behind obstacles or around corners. Recent studies on passive NLOS mainly focus on steady-state measurement and reconstruction methods, which show limitations in recognition of moving targets. To the best of our knowledge, we propose a novel event-based passive NLOS imaging method. We acquire asynchronous event-based data which contains detailed dynamic information of the NLOS target, and efficiently ease the degradation of speckle caused by movement. Besides, we create the first event-based NLOS imaging dataset, NLOS-ES, and the event-based feature is extracted by time-surface representation. We compare the reconstructions through event-based data with frame-based data. The event-based method performs well on PSNR and LPIPS, which is 20% and 10% better than frame-based method, while the data volume takes only 2% of traditional method.
@article{arxiv.2209.13300,
title = {Passive Non-line-of-sight Imaging for Moving Targets with an Event Camera},
author = {Conghe Wang and Yutong He and Xia Wang and Honghao Huang and Changda Yan and Xin Zhang and Hongwei Chen},
journal= {arXiv preprint arXiv:2209.13300},
year = {2023}
}