Point cloud registration is a basic and important research topic in computer vision.Aiming at the problems of existing registration algorithms that sensitive initial values and poor universality on feature descriptors,this paper proposes a two-step registration method including manual rough registration and ICP fine registration based on new weighted factor and new feature descriptors.The normal calculation of the point cloud can adequately describe the characteristics and weighting factors of point cloud descriptors.In the precision registration,the nearest point is queried according to the feature distance,the feature distance between point clouds is constantly calculated,and the mismatched point pairs are removed according to the 3σ criterion,thus achieving the effect of accelerating convergence and improving accuracy.The results show that compared with the traditional ICP algorithm,the convergence time of the proposed algorithm is only 20％,and the final registration error is reduced to 0.008 mm.
point cloud registrationiteration closest pointHarris3D algorithmfeature descriptorfine registration
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