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Improved Point Cloud Registration with Scale Invariant Feature Extracted

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Journal of Russian Laser Research Aims and scope

Abstract

The efficiency and accuracy of point set registration is always a challenge to deal with. In this paper, we propose an improved algorithm using a scale invariant feature extracted. The larger transformation scale and rotation angle cause lower registration accuracy. The initial corresponding point set can be obtained using a scale invariant feature transform (SIFT) operator. In addition, the geometric features of the points are combined to remove the wrong points. The unit quaternion algorithm is used to estimate the best rigid body transformation matrix for precise registration. The experiments show that the registration accuracy increases by 7.99%, while the time consumption decreased by 6.24% in a typical indoor scene.

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Authors and Affiliations

  1. Changchun University of Science and Technology, National Demonstration Center for Experimental Optoelectronic Engineering Education, 7089 Weixing Road, Changchun City, 130022, Jilin Province, China

    Qinglong Hu, Jiayu Niu, Zhiwei Wang & Shifeng Wang

  2. Changchun University of Science and Technology, Key Laboratory of Optoelectronic Measurement and Optical Information Transmission Technology, 7089 Weixing Road, Changchun City, 130022, Jilin Province, China

    Shifeng Wang

Authors
  1. Qinglong Hu
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  2. Jiayu Niu
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  3. Zhiwei Wang
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  4. Shifeng Wang
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Correspondence to Shifeng Wang.

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Hu, Q., Niu, J., Wang, Z. et al. Improved Point Cloud Registration with Scale Invariant Feature Extracted. J Russ Laser Res 42, 219–225 (2021). https://doi.org/10.1007/s10946-021-09953-6

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  • DOI: https://doi.org/10.1007/s10946-021-09953-6

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