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A Fast Weighted Registration Method of 3D Point Cloud Based on Curvature Feature

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Published:16 March 2018Publication History

ABSTRACT

In order to realize the fast and accurate registration of 3D point cloud data, a new fast weighted registration method is proposed in this paper. Firstly, using curvature feature, the method samples the original 3D point cloud data to quickly find matching points and remove wrong point pairs. Secondly, by introducing the iterative re-weighted least squares (IRLS) algorithm, the method carries out coarse alignment of the scattered point cloud. Finally, the method presents an improved distance-weighted Iterative Closest Point (ICP) algorithm to achieve fine matching. The experimental results show that the method has good convergence, robustness and accuracy.

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  1. A Fast Weighted Registration Method of 3D Point Cloud Based on Curvature Feature

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      cover image ACM Other conferences
      ICMIP '18: Proceedings of the 3rd International Conference on Multimedia and Image Processing
      March 2018
      125 pages
      ISBN:9781450364683
      DOI:10.1145/3195588

      Copyright © 2018 ACM

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      Publication History

      • Published: 16 March 2018

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