Feng Xiaohua, Gao Liang
University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States.
University of Illinois at Urbana-Champaign, Beckman Institute for Advanced Science and Technology, Urbana, Illinois, United States.
Opt Eng. 2019 Jun;58(6). doi: 10.1117/1.OE.58.6.060501. Epub 2019 Jun 5.
Structured-light depth cameras rely on projecting and resolving coded patterns on a three-dimensional scene with high contrast. The front-end optics of such depth cameras impose a fundamental restriction on the depth-sensing range and accuracy: the patterns only remain sharp within the depth of field jointly determined by the camera and projector. We present here a robust method to improve the depth-sensing range and accuracy for a structured-light depth camera without changing the underlying optical design. Moreover, it shows the unique advantage in macrophotography of highly light-scattering objects. We analyze the proposed method theoretically and validate it in experiments.
结构光深度相机依靠在具有高对比度的三维场景上投射和解码图案。此类深度相机的前端光学器件对深度感知范围和精度施加了基本限制：图案仅在由相机和投影仪共同确定的景深范围内保持清晰。我们在此提出一种稳健的方法，可在不改变基础光学设计的情况下提高结构光深度相机的深度感知范围和精度。此外，它在对高散射物体的微距摄影中展现出独特优势。我们从理论上分析了所提出的方法，并通过实验对其进行了验证。
