Evaluating point cloud accuracy of static three-dimensional laser scanning based on point cloud error ellipsoid model

Abstract

Evaluation of static three-dimensional (3-D) laser scanning point cloud accuracy has become a topical research issue. Point cloud accuracy is typically estimated by comparing terrestrial laser scanning data related to a finite number of check point coordinates against those obtained by an independent source of higher accuracy. These methods can only estimate the point accuracy but not the point cloud accuracy, which is influenced by the positional error and sampling interval. It is proposed that the point cloud error ellipsoid is favorable for inspecting the point cloud accuracy, which is determined by the individual point error ellipsoid volume. The kernel of this method is the computation of the point cloud error ellipsoid volume and the determination of the functional relationship between the error ellipsoid and accuracy. The proposed point cloud accuracy evaluation method is particularly suited for small sampling intervals when there exists an intersection of two error ellipsoids, and is suited not only for planar but also for nonplanar target surfaces. The performance of the proposed method (PM) is verified using both planar and nonplanar board point clouds. The results demonstrate that the proposed evaluation method significantly outperforms the existing methods when the target surface is nonplanar or there exists an intersection of two error ellipsoids. The PM therefore has the potential for improving the reliability of point cloud digital elevation models and static 3-D laser scanning-based deformation monitoring.