Revisiting Optimal Coding for I-ToF under Practical Sensor Constraints

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.