Köhler Niklas Alexander, Geis Marcel, Nöh Claudius, Mielke Alexandra, Groß Volker, Lange Robert, Sohrabi Keywan, Frey Jochen
Department of Health, University of Applied Sciences Mittelhessen, 35390 Giessen, Germany.
Institute of Safety and Security Research (ISF), Hochschule Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany.
Sensors (Basel). 2024 Dec 27;25(1):109. doi: 10.3390/s25010109.
Because of their resilience, Time-of-Flight (ToF) cameras are now essential components in scientific and industrial settings. This paper outlines the essential factors for modeling 3D ToF cameras, with specific emphasis on analyzing the phenomenon known as "wiggling". Through our investigation, we demonstrate that wiggling not only causes systematic errors in distance measurements, but also introduces periodic fluctuations in statistical measurement uncertainty, which compounds the dependence on the signal-to-noise ratio (SNR). Armed with this knowledge, we developed a new 3D camera model, which we then made computationally tractable. To illustrate and evaluate the model, we compared measurement data with simulated data of the same scene. This allowed us to individually demonstrate various effects on the signal-to-noise ratio, reflectivity, and distance.
由于其具有的弹性,飞行时间(ToF)相机现已成为科学和工业环境中的重要组件。本文概述了对3D ToF相机进行建模的关键因素,特别着重于分析被称为“摆动”的现象。通过我们的研究,我们证明摆动不仅会在距离测量中导致系统误差,还会在统计测量不确定性中引入周期性波动,这加剧了对信噪比(SNR)的依赖。基于这一认识,我们开发了一种新的3D相机模型,然后使其在计算上易于处理。为了说明和评估该模型,我们将测量数据与同一场景的模拟数据进行了比较。这使我们能够分别展示对信噪比、反射率和距离的各种影响。