在实际传感器约束下重新审视 I-ToF 的最优编码
Revisiting Optimal Coding for I-ToF under Practical Sensor Constraints
为 I-ToF 深度传感器提供了一种在硬件约束下基于解析误差传播指标搜索调制/解调编码方案的思路，可替代依赖大规模深度学习优化的编码设计，直接提升深度重建精度。
原文依据 we first analyze the error-propagation process in I-ToF depth sensing and derive a new metric for guiding the design and search of coding schemes
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论间接飞行时间（I-ToF）相机的深度精度高度依赖其编码方案。然而，由于调制与解调函数的可能组合无穷多，识别最优编码方案颇具挑战。尽管已有工作推导出用于指导编码方案设计的深度精度指标，但它们要么不满足真实 I-ToF 器件的约束，要么严重依赖大规模深度学习优化。在本工作中，我们首先分析 I-ToF 深度传感中的误差传播过程，并推导出一个用于指导编码方案设计与搜索的新指标。随后，我们将 I-ToF 传感器的实际硬件约束直接纳入编码方案设计，这大幅缩小了可行调制与解调函数的空间，使基于指标的搜索变得可行。通过我们的搜索方法得到的编码方案在仿真和真实实验中均优于先前的方案。
英文原文摘要 997 字符
The depth precision of an indirect time-of-flight (I-ToF) camera is highly dependent on its coding scheme. However, identifying the optimal coding scheme is challenging due to the infinitely many possible combinations of modulation and demodulation functions. Although previous works have derived depth-precision metrics to guide coding-scheme design, they either do not satisfy the constraints of real-world I-ToF devices or rely heavily on large-scale deep-learning optimization. In this work, we first analyze the error-propagation process in I-ToF depth sensing and derive a new metric for guiding the design and search of coding schemes. Then we incorporate practical hardware constraints of I-ToF sensors directly into the coding-scheme design, which greatly reduces the space of feasible modulation and demodulation functions and makes metric-based search feasible. The coding schemes obtained by our search method outperform previous schemes in both simulations and real-world experiments.