A fast point cloud registration algorithm is proposed for the problem that the traditional cpd (Coherent Point Drift) algorithm is time consuming and has poor the registration efficiency. Firstly, the voxel grid metho...
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ISBN:
(纸本)9789881563958
A fast point cloud registration algorithm is proposed for the problem that the traditional cpd (Coherent Point Drift) algorithm is time consuming and has poor the registration efficiency. Firstly, the voxel grid method is carried out on the three-dimensional bounding box of the cloud space, and the point in the whole voxel are expressed by the voxel centers, and the down-sampling operation of the cloud is completed to reduce the amount of the calculated data. Then, the Gaussian mixture model is established for the obtained point cloud to compute the values of negative log-likelihood functions. Finally, we use the EM algorithm to iterate to solve the closed parameters by minimizing negative logarithmic likelihood function. The rotation matrix and translation vector are obtained to match two points clouds. The experimental results show that the proposed method can greatly improve the registration speed while maintaining the original registration accuracy.
A fast point cloud registration algorithm is proposed for the problem that the traditional cpd（Coherent Point Drift）algorithm is time consuming and has poor the registration ***,the voxel grid method is carried out ...
详细信息
A fast point cloud registration algorithm is proposed for the problem that the traditional cpd（Coherent Point Drift）algorithm is time consuming and has poor the registration ***,the voxel grid method is carried out on the three-dimensional bounding box of the cloud space,and the point in the whole voxel are expressed by the voxel centers,and the down-sampling operation of the cloud is completed to reduce the amount of the calculated ***,the Gaussian mixture model is established for the obtained point cloud to compute the values of negative log-likelihood ***,we use the EM algorithm to iterate to solve the closed parameters by minimizing negative logarithmic likelihood *** rotation matrix and translation vector are obtained to match two points *** experimental results show that the proposed method can greatly improve the registration speed while maintaining the original registration accuracy.
This paper proposes a novel method via dynamic tree to solve the non-rigid registration of point sets with large shape difference which is a difficult problem for existing methods. Affine ICP algorithm with bidirectio...
详细信息
ISBN:
(纸本)9781467371896
This paper proposes a novel method via dynamic tree to solve the non-rigid registration of point sets with large shape difference which is a difficult problem for existing methods. Affine ICP algorithm with bidirectional distance is employed to evaluate the similarity between two point sets, and then non-rigid registration is conducted on similar models and subjects. Subjects with accurate registration results are added in the dynamic tree. These steps are repeated until all subjects are linked in the tree. Therefore, large shape difference is divided into several small deformations by the intermediate point sets, and the registration results of model and every subject in the tree are satisfactory. Experimental results show that our method incredibly improves the accuracy of the registration with two point sets bearing large shape difference compared with existing approaches.
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