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This paper proposes a coarse-to-fine registration algorithm for 3D point cloud. A novel feature points extraction method is presented, following an integrated local feature descriptor including Gaussian curvature, average curvature and point density for each point, through which we can achieve the coarse registration. Then, the ICP method is employed to refine the registration results with a good initial guess. Experiments including different simulated data sets demonstrate the applicability of the proposed methods. Meanwhile, the proposed coarse-to-fine registration algorithm is demonstrated to be robust to common nuisances, including noise and varying point cloud resolutions, and can achieve high accuracy and computation efficiency.

A Novel Coarse-to-fine Registration for 3D Point Cloud Based on Feature Points