Automated registration of dense terrestrial laser-scanning point clouds using curves

Abstract

This paper proposes an automatic method for registering terrestrial laser scans in terms of robustness and accuracy. The proposed method uses spatial curves as matching primitives to overcome the limitations of registration methods based on points, lines, or patches as primitives. These methods often have difficulty finding correspondences between the scanned point clouds of freeform surfaces (e.g., statues, cultural heritage). The proposed method first clusters visually prominent points selected according to their associated geometric curvatures to extract crest lines which describe the shape characteristics of point clouds. Second, a deformation energy model is proposed to measure the shape similarity of these crest lines to select the correct matching-curve pairs. Based on these pairs, good initial orientation parameters can be obtained, resulting in fine registration. Experiments were undertaken to evaluate the robustness and accuracy of the proposed method, demonstrating a reliable and stable solution for accurately registering complex scenes without good initial alignment.