Planar Feature Constrained Point Cloud Registration Method with Minimal Overlap Structure

Based on the spatial feature association of point clouds from different 3D laser scanning data and the characteristics of regular plane features in urban structure scenes, a low overlap structure point cloud registration method based on plane feature constraint is proposed in this paper. Firstly, a planar feature descriptor is proposed based on the distribution and density of points in the plane feature extraction to reduce the influence of broken plane and pseudo plane on the registration accuracy. Furthermore, a registration method based on the planar feature constraints is designed. The method incorporates geometric feature descriptor based on planar information and mathematical equation of feature plane to solve the spatial transformation matrix iteratively. To verify the Correctness and effectiveness, the proposed method is compared with three main classic registration algorithms on structure scene data. The experimental results demonstrate that the proposed registration method achieves the satisfied results and is superior to other algorithms both in accuracy and efficiency.