发表机构
Universidad de Zaragoza–I3A; University of Wisconsin–Madison（萨拉戈萨大学-阿拉贡工程研究所（I3A）; 威斯康星大学麦迪逊分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出级联非视距成像方法，利用高阶光子信息，结合超快激光扫描和时间门控传感器，实现对多拐角隐藏物体的四跳和五跳成像，并分析粗糙墙壁影响，支持多视角观察。
AI 中文摘要
飞行时间非视距（NLOS）成像通过分析可见（中继）墙壁上散射的间接光子的飞行时间，来恢复隐藏物体的信息。大多数方法做出简化假设，即光子仅沿三跳路径传播，从而忽略了高阶光子（例如四跳或五跳路径）中编码的其他有用信息。我们提出了一种新颖的级联非视距成像方法，该方法利用高阶信息，能够对更广泛的单拐角和多拐角场景进行成像。我们将超快激光扫描与最新的时间门控二维传感器阵列相结合，以捕获场景在可见中继墙壁上的脉冲响应。根据捕获的脉冲响应，我们的方法计算任何其他隐藏墙壁上的类似虚拟脉冲响应。这有效地使我们能够串联第二个虚拟非视距成像系统，该系统利用高阶照明。我们在仿真和真实原型中验证了我们的级形成像方法，展示了在具有挑战性的方向和隐藏在两个拐角周围的物体上使用四跳和五跳照明进行非视距成像。我们还分析了基于波的非视距成像如何与粗糙的隐藏墙壁相互作用，这解释并有助于克服现有的可见性限制。我们进一步说明了如何通过依赖多个隐藏墙壁，从不同视角对隐藏物体进行成像，从而观察以前未见过的特征。
英文摘要
Time-of-flight non-line-of-sight (NLOS) imaging recovers information from hidden objects by analyzing the time of flight of indirect photons scattered on a visible (relay) wall. Most methods make the simplifying assumption that photons travel exclusively three-bounce paths, thus ignoring other useful information encoded in higher-order photons (with, e.g., four- or five-bounce paths). We present a novel cascaded NLOS imaging approach that leverages higher-order information and allows imaging a broader range of single- and multi-corner scenarios. We combine ultra-fast laser scanning with recent time-gated 2D sensor arrays to capture the scene's impulse response on a visible relay wall. From the captured impulse response, our method computes an analogous virtual impulse response at any other hidden wall. This effectively allows us to concatenate a second, virtual NLOS imaging system that leverages higher-order illumination. We validate our cascaded imaging method both in simulation and with a real prototype, demonstrating NLOS imaging with fourth- and fifth-bounce illumination of objects in challenging orientations and hidden around two corners. We also analyze how wave-based NLOS imaging interacts with rough hidden walls, which explains and helps overcome existing visibility limitations. We further illustrate how to image hidden objects from different perspectives, thus observing previously unseen features, by relying on multiple hidden walls.
Comments18 pages, 21 figures. See https://graphics.unizar.es/projects/CascadedNLOS/
Journal refACM Transactions on Graphics. 45, 6, Article 205 (SIGGRAPH Asia 2026)
DOI：10.1145/3842503
