Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics

Abstract

Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target-free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state-of-the-art equivalents. The results also indicate that least squares plane fitting is the best technique for MLS point cloud registration.