论文标题
通过事件摄像机进行移动目标的被动非视线成像
Passive Non-line-of-sight Imaging for Moving Targets with an Event Camera
论文作者
论文摘要
非视线（NLOS）成像是一种用于检测障碍物后面或角落周围物体的新兴技术。关于被动NLOS的最新研究主要集中在稳态测量和重建方法上，这些方法显示出识别移动目标的局限性。据我们所知，我们提出了一种新型的基于事件的无源NLOS成像方法。我们获取基于异步事件的数据，其中包含NLOS目标的详细动态信息，并有效地减轻了由运动引起的斑点降解。此外，我们创建了第一个基于事件的NLOS成像数据集NLOS-ES，并且通过时间表面表示提取了基于事件的功能。我们通过基于事件的数据与基于框架的数据比较重建。基于事件的方法在PSNR和LPIP上表现良好，该方法比基于框架的方法好20％和10％，而数据量仅占传统方法的2％。
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.
