Abstract
Light detection and ranging (LiDAR) generating point clouds is rapidly expected to apply to the road monitoring. However, existing methods for co-registration of two sets of point clouds, such as Iterative Closest Point (ICP) method, are not robust against the occlusion caused by pedestrians or vehicles. Therefore, this paper presents a method that achieves accurate co-registration of the point clouds even though the data are occluded. The proposed method composes of two processing. The first processing takes step-by-step correction for a rough co-registration by utilizing normal derived from planes vertically standing, e.g. building wall surfaces and. After the rough correction is completed, the second processing utilizing ICP method is implemented for an accurate co-registration. In the experiments, we used the point clouds observed by using terrestrial LiDAR data, and the parts of the point clouds were excluded, representing the occlusion by objects. The validation results show that the proposed method achieved a high accuracy even for the occluded data.
