Research on Partial Overlapping Point Cloud Registration Algorithm for Matching Geometric Features.

In order to solve the problems of outlier, redundant points and fuzzy features in the registration of partially overlapping point clouds, a new registration algorithm for partially overlapping point clouds matching geometric features is proposed. Feature interaction and multilayer perceptron are used to calculate the overlap score and feature salient value of each point to be registered, and extract the salient feature points in the overlapping area. Geometric features are captured according to length and angle, representative feature descriptors are extracted, special geometric feature matching networks are designed, internal values and outlier of key points are identified, and outlier are filtered. The registration results are obtained using weighted singular value decomposition operations. Experimental results show that for ModelNet40 dataset, compared with the benchmark algorithm, the root mean square error and mean absolute error of the proposed algorithm in rotation and translation are reduced by 59%, 45%, 83% and 66% respectively. For the ShapeNetCore dataset, the algorithm is reduced by 63%, 32%, 78%, and 50% in four indicators, respectively. [ABSTRACT FROM AUTHOR]