Abstract
In order to solve the problems of long time consuming and easy failure of the existing coarse registration algorithms based on global registration on two 3D point clouds with low overlap rate, we proposed a coarse registration algorithm based on feature regions and the Super 4-Points Congruent Sets (SUPER4PCS) algorithm. Firstly, intrinsic shape signatures (ISS) algorithm was used to extract and describe the features of the down-sampled point clouds. Secondly, the feature point clouds were divided into regions and the initial overlapped sub-regions were extracted. Thirdly, the complete overlapping regions were grown from the overlapped sub-regions and gradually recovered. Finally, the SUPER4PCS was used for registration on the complete overlapping regions. The experimental results showed that the geometric accuracy, registration success rate, and robustness of the proposed algorithm were better than that of SUPER4PCS and its improved algorithms, and the time consumption was one order of magnitude lower than that of SUPER4PCS on point clouds with low overlap rate.
Published Version
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