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Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm.

Higinio Mora1, Jerónimo M Mora-Pascual1, Alberto García-García1

  • 1Specialized Processor Architecture Laboratory, Department of Computer Technology and Computation, University of Alicante, Alicante, Spain.

Plos One
|October 22, 2016
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Summary
This summary is machine-generated.

This study introduces faster Iterative Closest Point (ICP) algorithm registration by using Chebyshev and Manhattan distances instead of Euclidean distance. This optimization speeds up 3D surface alignment by 14% without compromising accuracy.

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Area of Science:

  • Robotics and Computer Vision
  • Computational Geometry

Background:

  • The Iterative Closest Point (ICP) algorithm is a standard for rigid registration in robotics and computer vision.
  • ICP's popularity stems from its simplicity in aligning 2D/3D surfaces.
  • High computational cost in certain ICP phases limits its real-time applications.

Purpose of the Study:

  • To propose an efficient approach to optimize the matching phase of the ICP algorithm.
  • To reduce the computational burden of the ICP algorithm's main bottleneck.
  • To enhance the performance and applicability of ICP in computationally intensive scenarios.

Main Methods:

  • Replaced the classic Euclidean distance metric with low-computational-cost alternatives.
  • Investigated Chebyshev and Manhattan distance metrics for point-to-point matching.
  • Conducted experiments using diverse 3D shapes, partial data, and noisy conditions.

Main Results:

  • Achieved an average speed-up of 14% in the ICP algorithm's execution time.
  • Demonstrated that the proposed method preserves the convergence properties of ICP.
  • Validated the robustness and quality of the registration results across various experimental setups.

Conclusions:

  • The use of Chebyshev and Manhattan distances offers a significant efficiency improvement for the ICP algorithm.
  • This optimization enhances ICP's suitability for applications requiring faster 3D surface registration.
  • The proposed method provides a practical solution for accelerating ICP without sacrificing accuracy.