A non-rigid automatic registration method of multi-temporal mobile laser scanning point clouds based on road short marking features

Abstract Because of the Global Navigation Satellite System (GNSS) signal occlusion, inertial measurement unit drift and other factors on positioning, location deviations of multi-temporal mobile laser scanning (MLS) point clouds collected in the same region are always exist. In order to improve the quality of multi-temporal MLS point clouds, it is necessary to correct the location deviations by point cloud registration. This work presents a non-rigid automatic registration method of multi-temporal MLS laser point clouds based on the characteristics of short road markings. Specifically, the central points at both end edges of short road markings were extracted as control points. The correspondences between control points in different point clouds were obtained by KD-tree and optimized by polygon similarity and Otsu methods. Then, based on the GNSS time and coordinate difference of true correspondences, the mathematical model of non-rigid registration adjustment was constructed by combining with gross error detection and polynomial fitting. Finally, multi-temporal MLS point clouds were registered according to the GNSS time and adjustment results. Validation results demonstrate that the registration accuracy reaches up to 2.8 cm. The proposed method provides a new way for high-precision fusion and change detection of multi-temporal MLS point clouds in road scenes.