High-Capacity Spatial Structured Light for Robust and Accurate Reconstruction

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 10; p. 4685
• Main Authors: Gu, Feifei, Du, Hubing, Wang, Sicheng, Su, Bohuai, Song, Zhan
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 12.05.2023; MDPI
• Subjects: 3D reconstruction; Accuracy; Algorithms; Coding; Corner detection; Dimensional measurement; high capacity; Pattern generation; pseudo-2D coding strategy; spatial structured light; spatial structured light; pseudo-2D coding strategy; corner detection; 3D reconstruction; high capacity
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23104685

Spatial structured light (SL) can achieve three-dimensional measurements with a single shot. As an important branch in the field of dynamic reconstruction, its accuracy, robustness, and density are of vital importance. Currently, there is a wide performance gap of spatial SL between dense reconstruction (but less accurate, e.g., speckle-based SL) and accurate reconstruction (but often sparser, e.g., shape-coded SL). The central problem lies in the coding strategy and the designed coding features. This paper aims to improve the density and quantity of reconstructed point clouds by spatial SL whilst also maintaining a high accuracy. Firstly, a new pseudo-2D pattern generation strategy was developed, which can improve the coding capacity of shape-coded SL greatly. Then, to extract the dense feature points robustly and accurately, an end-to-end corner detection method based on deep learning was developed. Finally, the pseudo-2D pattern was decoded with the aid of the epipolar constraint. Experimental results validated the effectiveness of the proposed system.