Automated markerless registration of point clouds from TLS and structured light scanner for heritage documentation

Abstract Three-dimensional (3D) model is a major form of cultural heritage documentation. In most cases, the properties of digital artefacts (e.g. readability, coverage) are affected by the acquisition procedure (e.g. device, workflow, conditions) and the characteristics of the physical artefact (e.g. shape, size and materials). In this paper, we study how to combine two acquisition techniques to acquire detailed 3D models of large physical objects. Specifically, we combine two laser scanning instruments: terrestrial laser scanning (TLS) and structured light scanner (SLS). TLS provides millimeter-scale resolution with large field of view, while SLS provides sub-millimeter resolution for limited field of view. This paper focuses on the registration of SLS and TLS point clouds, a critical step, which aims at aligning the acquired point clouds in a common frame. Existing registration systems mostly rely on manual post-processing or marker-based alignment. Manual registration is however time consuming and tedious, while markers increase the complexity of scanning and are not always acceptable in cultural site documentation. Therefore, we propose an automated markerless registration and fusion pipeline for point clouds. Firstly, we replace the marker-based coarse alignment by an automated registration of SLS and TLS point clouds; secondly, we refine the alignment of SLS point clouds on TLS data using the Iterative Corresponding Point algorithm; finally, we seamless stitch the SLS and TLS point clouds by globally regularizing the registration error for the all the point clouds at once. Our experiments show the efficiency of the proposed approach on two real-world cases, involving detailed point clouds correctly aligned without requiring markers or manual tuning. This paper provides an operational process reference for automated markerless registration of multi-source point clouds.