Research on Point Cloud Registration Algorithm Based on Layered Interpolation and Multiple Perspectives
To solve the problems of large cumulative errors,poor registration accuracy,and low registration efficiency caused by multi view registration in 3D reconstruction of rough castings,this paper proposes a lay-ered interpolation multi view point cloud registration algorithm.Firstly,industrial cameras are used to prepro-cess point cloud information from different perspectives on casting objects;Secondly,feature points are ex-tracted through the angle characteristics of neighborhood normal vectors,and FPFH feature point descriptions are performed on them.An improved 4PCS algorithm is used for coarse registration of adjacent point clouds in each layer to obtain good initial positions.Then,the generalized iterative nearest point GICP algorithm ac-celerated by KD tree is used for fine registration;Finally,a layered interpolation multi view registration strate-gy is used to stitch together a complete point cloud.The experimental results show that the registration meth-od proposed in this paper reduces registration time by 96.5%,96.1%,and 88.3%respectively compared to the SAC-IA+ICP algorithm,4PCS+ICP algorithm,and Super-4PCS+ICP algorithm,and improves reg-istration accuracy by 79.5%,71.5%,and 55.1%,respectively.The registration quality of the algorithm in this article is not only better than that of sequential multi view registration,but also has obvious advantages in robustness and accurate registration,providing an efficient method for subsequent 3D reconstruction.
3D point cloud registrationmulti perspective stitchingneighborhood feature point extraction4PCS
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