Phase-SLAM: Mobile Structured Light Illumination for Full Body 3D Scanning

Abstract

Full body scanning plays an important role in automated industrial manufacture and inspection. It requires the fusion of multi-view point cloud data and consumes large computational resources when the geometry of corresponding point clouds are unknown. Structured Light Illumination (SLI) is one of the most promising indoor 3D imaging techniques, but also has the same weakness for fusing the multi-view point clouds. This work proposes a mobile SLI system to alleviate this problem for full body 3D scanning. We derive the geometric relation between the phase and the motion of the mobile system, and develop an optimization approach to estimate the pose by comparing the phase image pair before and after the motion. Further more, a graph-based Simultaneous Localization And Mapping (SLAM) framework is built to improve the global accuracy of the pose estimation. By using the 2D phase comparison, the proposed method is more accurate than the normal 2D image feature point matching, and has lower computational complexity than the 3D point registration. The proposed system is experimented in both 3D Simulator and real environment. The yielded full body scan results demonstrated its higher accuracy and more efficiency than the current methods.