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Robust iterative closest point algorithm based on global reference point for rotation invariant registration.

Shaoyi Du1, Yiting Xu1, Teng Wan1

  • 1School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province, P.R., China.

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Summary
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This study introduces a novel Iterative Closest Point (ICP) algorithm variant for 3D point cloud registration. The enhanced ICP method improves accuracy and robustness, especially with large initial rotation angles.

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Area of Science:

  • Computer Vision
  • Computational Geometry
  • 3D Data Processing

Background:

  • Iterative Closest Point (ICP) algorithm is standard for rigid registration.
  • ICP algorithm struggles with large initial rotation angles and requires good initial parameters.
  • Failure of ICP can lead to inaccurate or failed 3D point cloud registration.

Purpose of the Study:

  • To develop a robust ICP algorithm variant for accurate 3D point cloud registration.
  • To overcome limitations of the standard ICP algorithm in handling large initial rotations.
  • To improve the reliability and accuracy of point cloud registration in challenging scenarios.

Main Methods:

  • Proposed a new objective function using rotation-invariant features based on Euclidean distance to a global reference point.
  • Employed a variant of the ICP algorithm for iterative optimization.
  • Established accurate correspondences using weighted rotation-invariant feature distance and position distance.
  • Solved rigid transformation using Singular Value Decomposition (SVD).
  • Implemented a coarse-to-fine registration strategy with monotonic convergence.

Main Results:

  • The proposed algorithm demonstrates enhanced accuracy and robustness compared to the original ICP algorithm.
  • Successful registration is achieved regardless of the initial rotation angle.
  • The algorithm shows monotonic convergence, ensuring stable registration.
  • Experimental results validate the superior performance of the new ICP variant.

Conclusions:

  • The novel ICP algorithm variant effectively addresses the limitations of traditional ICP for rigid registration.
  • The rotation-invariant feature and coarse-to-fine approach significantly improve robustness against large initial rotations.
  • This method offers a more reliable solution for 3D point cloud registration tasks.