We provide methods which recover planar scene geometry by utilizing the transient histograms captured by a class of close-range time-of-flight (ToF) distance sensor. A transient histogram is a one dimensional temporal waveform which encodes the arrival time of photons incident on the ToF sensor. Typically, a sensor processes the transient histogram using a proprietary algorithm to produce distance estimates, which are commonly used in several robotics applications. Our methods utilize the transient histogram directly to enable recovery of planar geometry more accurately than is possible using only proprietary distance estimates, and consistent recovery of the albedo of the planar surface, which is not possible with proprietary distance estimates alone. This is accomplished via a differentiable rendering pipeline, which simulates the transient imaging process, allowing direct optimization of scene geometry to match observations. To validate our methods, we capture 3,800 measurements of eight planar surfaces from a wide range of viewpoints, and show that our method outperforms the proprietary-distance-estimate baseline by an order of magnitude in most scenarios. We demonstrate a simple robotics application which uses our method to sense the distance to and slope of a planar surface from a sensor mounted on the end effector of a robot arm.

翻译：我们提供了一系列方法，通过利用近距离飞行时间（ToF）距离传感器捕获的瞬态直方图来恢复平面场景几何结构。瞬态直方图是一种一维时间波形，编码了入射到ToF传感器的光子到达时间。通常，传感器使用专有算法处理瞬态直方图以生成距离估计值，这些估计值常用于多种机器人应用。我们的方法直接利用瞬态直方图，能够更精确地恢复平面几何结构（优于仅使用专有距离估计值的效果），并一致地恢复平面表面的反照率（这是仅靠专有距离估计无法实现的）。这一目标通过可微分渲染管线实现：该管线模拟瞬态成像过程，允许直接优化场景几何以匹配观测数据。为验证方法有效性，我们从宽视角范围捕获了八个平面表面的3800次测量数据，结果表明，在多数场景中，我们的方法相较于基于专有距离估计的基线方法性能提升了一个数量级。我们展示了一个简单的机器人应用案例：通过安装在机械臂末端执行器上的传感器，利用本方法感知平面表面的距离与坡度。