Advertisement

Partial Alignment of Data Sets Based on Fast Intrinsic Feature Match

  • Yaxin Peng
  • Naiwu Wen
  • Xiaohuang Zhu
  • Chaomin ShenEmail author
Conference paper
  • 815 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11775)

Abstract

Point Feature Histograms (PFH) is a statistic and geometric invariant descriptor that has been widely used in shape analysis. Current PFH based feature extraction methods are highly affected by the time scale and become less effective for unbalanced cases, which limits their performance. In this paper, we focus on finding a framework for partial registration by an adaptive partition of point set algorithm. Firstly, we propose an adaptive partition method base on PFH coding. Secondly, we conduct a series of fast parallel implementations for efficiency. Thirdly, we plug in the PFH based partition method and trimmed strategy to our modified iterative closest point method. Experiments demonstrate that our algorithms are robust and stable.

Keywords

Partial registration PFH coding ICP Trimmed method 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant No. 11771276.

References

  1. 1.
  2. 2.
  3. 3.
    Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)CrossRefGoogle Scholar
  4. 4.
    Besl, P., McKay, N.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)CrossRefGoogle Scholar
  5. 5.
    Chen, J., Belaton, B., Pan, Z.: A robust subset-ICP method for point set registration. In: Zaman, H.B., Robinson, P., Olivier, P., Shih, T.K., Velastin, S. (eds.) IVIC 2013. LNCS, vol. 8237, pp. 59–69. Springer, Cham (2013).  https://doi.org/10.1007/978-3-319-02958-0_6CrossRefGoogle Scholar
  6. 6.
    Chen, Y., Medioni, G.: Object modelling by registration of multiple range images. Image Vis. Comput. 10(3), 145–155 (1992)CrossRefGoogle Scholar
  7. 7.
    Chetverikov, D., Stepanov, D., Krsek, P.: Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm. Image Vis. Comput. 23(3), 299–309 (2005)CrossRefGoogle Scholar
  8. 8.
    Dong, J., Peng, Y., Ying, S., Hu, Z.: LieTrICP: an improvement of trimmed iterative closest point algorithm. Neurocomputing 140, 67–76 (2014)CrossRefGoogle Scholar
  9. 9.
    Du, S., Guo, Y., Sanroma, G., Ni, D., Wu, G., Shen, D.: Building dynamic population graph for accurate correspondence detection. Med. Image Anal. 26(1), 256–267 (2015)CrossRefGoogle Scholar
  10. 10.
    Du, S., Zhu, J., Zheng, N., Liu, Y., Ce, L.: Robust iterative closest point algorithm for registration of point sets with outliers. Opt. Eng. 50(8), 087001 (2011)CrossRefGoogle Scholar
  11. 11.
    Du, S.Y., Zheng, N.N., Meng, G.F., Yuan, Z.J., Li, C.: Affine registration of point sets using ICP and ICA. IEEE Signal Process. Lett. 15, 689–692 (2008)CrossRefGoogle Scholar
  12. 12.
    Du, S.Y., Zheng, N.N., Ying, S.H., Liu, J.Y.: Affine iterative closest point algorithm for point set registration. Pattern Recogn. Lett. 31, 791–799 (2010)CrossRefGoogle Scholar
  13. 13.
    Johnson, A.E., Hebert, M.: Surface registration by matching oriented points. In: Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling, NRC 1997, p. 121. IEEE Computer Society (1997)Google Scholar
  14. 14.
    Peng, Y., Ying, S., Qin, J., Zeng, T.: Trimmed strategy for affine registration of point sets. J. Appl. Remote Sens. 7(1), 073468 (2013)CrossRefGoogle Scholar
  15. 15.
    Ying, S., Peng, J., Du, S., Qiao, H.: A scale stretch method based on ICP for 3D data registration. IEEE Trans. Autom. Sci. Eng. 6(3), 559–565 (2009)CrossRefGoogle Scholar
  16. 16.
    Ying, S., Peng, Y., Wen, Z.: Iwasawa decomposition: a new approach to 2D affine registration problem. Pattern Anal. Appl. 24(2), 127–137 (2011)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Zha, H., Ikuta, M., Hasegawa, T.: Registration of range images with different scanning resolutions. In: Proceedings of the IEEE International Conference on System, Man, Cybernetics, Nashville, Tennessee, USA, pp. 1495–1500 (2000)Google Scholar
  18. 18.
    Zhang, Z.: Iterative point matching for registration of free form surfaces. Int. J. Comput. Vision 13(2), 119–152 (1994)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yaxin Peng
    • 1
  • Naiwu Wen
    • 1
  • Xiaohuang Zhu
    • 1
  • Chaomin Shen
    • 2
    Email author
  1. 1.Department of Mathematics, School of ScienceShanghai UniversityShanghaiChina
  2. 2.Department of Computer ScienceEast China Normal UniversityShanghaiChina

Personalised recommendations