Signal Separation Coding for Robust Depth Imaging Based on Structured Light

This paper presents an original approach to coding the light patterns for robust depth imaging based on structured light. We have discovered that the degradation of precision and robustness, seen in most conventional approaches to structured light, comes mainly from the overlapping of multiple codes in the signal received at a camera pixel, where the overlapped codes are from the neighbouring and/or, even, distant pixels of the projecting mirror array. Considering the criticality of separating the overlapped codes to precision and robustness, we propose a novel signal separation code, referred to here as “Hierarchical Orthogonal Code (HOC),” for depth imaging. HOC provides not only the separation of overlapped codes, but also a robust decision on pixel correspondence with error correction based on a contextual likelihood among the sets of separated codes from neighbouring camera pixels. The experimental results have shown that the proposed HOC significantly enhances the robustness and precision in depth imaging, compared to the best known conventional approaches. The proposed approach opens a greater feasibility of applying structured light based depth imaging to a 3D modelling of cluttered workspace for home service robots.