Passive Non-line-of-sight Imaging for Moving Targets with an Event Camera
Conghe Wang (1), Yutong He (2), Xia Wang (1), Honghao Huang (2),, Changda Yan (1), Xin Zhang (1), Hongwei Chen (2)((1) Key Laboratory of, Photoelectronic Imaging Technology, System of Ministry of Education of, China, School of Optics, Photonics

TL;DR
This paper introduces a novel event-based passive NLOS imaging technique that effectively captures moving targets behind obstacles, outperforming traditional frame-based methods in quality and efficiency.
Contribution
The paper presents the first event-based NLOS imaging method and dataset, improving dynamic target recognition and reducing data volume compared to existing approaches.
Findings
Event-based method outperforms frame-based in PSNR and LPIPS by 20% and 10%.
Event data volume is only 2% of traditional methods.
Created the first dataset for event-based NLOS imaging.
Abstract
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…
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Taxonomy
TopicsAdvanced Optical Sensing Technologies · Atomic and Subatomic Physics Research · Radiation Detection and Scintillator Technologies
