用单光子激光雷达从一次测量中恢复遮挡和镜面场景的3D结构
Shoot-Bounce-3D: Single-Shot Occlusion-Aware 3D from Lidar by Decomposing Two-Bounce Light
- 通过数据驱动方法分解多跳光信号,解析出每个激光点的独立贡献
- 首次在10万组模拟数据上训练,实现单次照射下遮挡区域的3D重建
- 适用于有镜子、遮挡物的复杂室内场景,适合自动驾驶与机器人感知
从单次测量中进行3D场景重建极具挑战性,尤其在存在遮挡区域和镜面材质时。本文利用单光子激光雷达,其不仅能捕捉直接反射光,还能捕获在场景中多次反射后到达传感器的光。这些多跳光包含可用于恢复稠密深度、被遮挡几何结构及材质属性的额外信息。以往研究仅在逐点扫描的条件下验证了这些能力,而本文聚焦更实际但更复杂的多点同时照明场景。由于多重照明、双跳光、阴影和镜面反射的共同影响,光传输过程难以解析。为此,我们提出一种数据驱动方法来反演单光子激光雷达中的光传输。为支持该方法,我们构建了首个包含约10万组室内场景激光瞬态的大型仿真数据集。利用该数据集学习复杂光传输先验,使测量到的双跳光可被分解为各激光点的独立贡献。最后,我们在实验中验证了这一分解方法如何用于从单次测量中推断具有遮挡和镜面的场景3D结构。代码与数据集已公开于https://shoot-bounce-3d.github.io。
原文摘要 · Abstract (English)
3D scene reconstruction from a single measurement is challenging, especially in the presence of occluded regions and specular materials, such as mirrors. We address these challenges by leveraging single-photon lidars. These lidars estimate depth from light that is emitted into the scene and reflected directly back to the sensor. However, they can also measure light that bounces multiple times in the scene before reaching the sensor. This multi-bounce light contains additional information that can be used to recover dense depth, occluded geometry, and material properties. Prior work with single-photon lidar, however, has only demonstrated these use cases when a laser sequentially illuminates one scene point at a time. We instead focus on the more practical - and challenging - scenario of illuminating multiple scene points simultaneously. The complexity of light transport due to the combined effects of multiplexed illumination, two-bounce light, shadows, and specular reflections is challenging to invert analytically. Instead, we propose a data-driven method to invert light transport in single-photon lidar. To enable this approach, we create the first large-scale simulated dataset of ~100k lidar transients for indoor scenes. We use this dataset to learn a prior on complex light transport, enabling measured two-bounce light to be decomposed into the constituent contributions from each laser spot. Finally, we experimentally demonstrate how this decomposed light can be used to infer 3D geometry in scenes with occlusions and mirrors from a single measurement. Our code and dataset are released at https://shoot-bounce-3d.github.io.
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