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Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers

机译:使用即插即用点云去噪器从单光子激光雷达数据进行实时3D重建

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摘要

Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of time required for the analysis of the recorded data. Here we show a new computational framework for real-time three-dimensional (3D) scene reconstruction from single-photon data. By combining statistical models with highly scalable computational tools from the computer graphics community, we demonstrate 3D reconstruction of complex outdoor scenes with processing times of the order of 20 ms, where the lidar data was acquired in broad daylight from distances up to 320 metres. The proposed method can handle an unknown number of surfaces in each pixel, allowing for target detection and imaging through cluttered scenes. This enables robust, real-time target reconstruction of complex moving scenes, paving the way for single-photon lidar at video rates for practical 3D imaging applications.
机译:单光子激光雷达已成为通过严峻环境进行深度成像的主要候选技术。到目前为止,主要的限制是分析记录的数据需要大量的时间。在这里,我们展示了一种用于从单光子数据进行实时三维(3D)场景重建的新计算框架。通过将统计模型与来自计算机图形社区的高度可扩展的计算工具相结合,我们演示了复杂室外场景的3D重建,其处理时间约为20µms,其中激光雷达数据是在日光下从320µm的距离采集的。所提出的方法可以处理每个像素中未知数量的表面,从而可以通过杂乱的场景进行目标检测和成像。这样就可以对复杂的运动场景进行鲁棒的实时目标重建,从而为单光子激光雷达在实际3D成像应用中的视频速率铺平了道路。

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