Accurate deformation analysis based on point position uncertainty estimation and adaptive projection point cloud comparison

Abstract

The accuracy of the scanning scene representation and corresponding points extraction are key factors in deformation analysis based on point cloud. Still, little is known about the influence of terrestrial laser scanner (TLS) survey properties on point cloud. In our study, an accurate deformation analysis method based on point position uncertainty estimation and adaptive projection point cloud comparison is proposed, which consists of two parts: (1) Evaluating the influence of scanning geometry on point cloud quality to gain high accuracy points; (2) an adaptive projection radius and depth point cloud comparison algorithm is constructed for acquiring corresponding points and calculating the deformation. A regular geometry and a landslide point cloud are selected. Results show that the mean error and mean absolute deviation of the distance between corresponding points are –0.3 mm and 16.2 mm, which demonstrates the method can provide an effective solution for the deformation analysis of complex topography.

Keywords

• point cloud
• deformation analysis
• scanning geometry
• point position uncertainty
• adaptive projection point cloud comparison