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作者:

Qin, B. (Qin, B..) | Li, X. (Li, X..) | Jia, S. (Jia, S..) | Yang, A. (Yang, A..) | Qiu, H. (Qiu, H..)

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Scopus

摘要:

The main objective of this paper is to develop 3D point cloud alignment technique by using an improved absolute orientation algorithm based on unit quaternion. In this method, Scale Invariant Features Transform (SIFT) is used to find corresponding feature points, and Random Sample Consensus (RANSAC) is used as robust estimator to remove false matches in the point cloud group. The unit quaternion solution is employed for initial registration. After the initial registration of point clouds, this cannot meet the requirements of registration accuracy. Therefore, we need to achieve accurate registration on the basis of initial registration. The Iterative Closest Point (ICP) algorithm is one of the widely-used methods to cope with 3D registration. However, ICP is vulnerable to outliers and missing data, which severely compromises its performance. In this paper, Sparse Lp-norm based ICP algorithm is developed to achieve precise registration. Experimental results verified accuracy of the presented algorithm in point cloud registration. © 2015 IEEE.

关键词:

absolute orientation; RANSAC; SIFT

作者机构:

  • [ 1 ] [Qin, B.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Qin, B.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 3 ] [Li, X.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 4 ] [Li, X.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 5 ] [Jia, S.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 6 ] [Jia, S.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 7 ] [Yang, A.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 8 ] [Yang, A.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
  • [ 9 ] [Qiu, H.]College of Electronic and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 10 ] [Qiu, H.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China

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来源 :

2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics

年份: 2015

页码: 499-503

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 2

ESI高被引论文在榜: 0 展开所有

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中文被引频次:

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