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Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information

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  • Lei Peng
  • Guangyao Li
  • Mang Xiao
  • Li Xie

Abstract

Recently, the Coherent Point Drift (CPD) algorithm has become a very popular and efficient method for point set registration. However, this method does not take into consideration the neighborhood structure information of points to find the correspondence and requires a manual assignment of the outlier ratio. Therefore, CPD is not robust for large degrees of degradation. In this paper, an improved method is proposed to overcome the two limitations of CPD. A structure descriptor, such as shape context, is used to perform the auxiliary calculation of the correspondence, and the proportion of each GMM component is adjusted by the similarity. The outlier ratio is formulated in the EM framework so that it can be automatically calculated and optimized iteratively. The experimental results on both synthetic data and real data demonstrate that the proposed method described here is more robust to deformation, noise, occlusion, and outliers than CPD and other state-of-the-art algorithms.

Suggested Citation

  • Lei Peng & Guangyao Li & Mang Xiao & Li Xie, 2016. "Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-17, February.
    • Handle: RePEc:plo:pone00:0148483
    DOI: 10.1371/journal.pone.0148483
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    Cited by:

    1. Xuetao Zhang & Libo Jian & Meifeng Xu, 2018. "Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-15, May.

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