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A Parallelized Iterative Closest Point Algorithm for 3D View Fusion

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Supercomputing (ISUM 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 948))

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Abstract

The Iterative Closest Point Algorithm (ICP) is a widely used method in computer science and robotics, used for minimizing a distance metric between two set of points. Common applications of the ICP are object localization and position estimation. In this work, we introduce a parallel version of the ICP which significantly reduces the computational time, by performing fewer operations while maintaining a simple and highly parallelizable algorithm. Our proposal is based on the naive computation of closest pairs of points in two different sets, instead of comparing all possible pairs we approximate the closest pairs of points by means of searching in a plausible subset. The experiments are performed on a sample from the Stanford 3D Scanning Repository, used for the 3D cloud of points registration. For these case studies, the error, as well as the solution, are exactly the same than using the exact algorithm.

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Authors and Affiliations

  1. Universidad de Guanajuato, DICIS, Carr. Palo Blanco-Valle de Santiago km 3.5 + 1.8, 36700, Salamanca, Guanajuato, Mexico

    S. Ivvan Valdez & Felipe Trujillo-Romero

Authors
  1. S. Ivvan Valdez
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  2. Felipe Trujillo-Romero
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Corresponding author

Correspondence to S. Ivvan Valdez .

Editor information

Editors and Affiliations

  1. University of Guadalajara, Guadalajara, Jalisco, Mexico

    Moises Torres

  2. Instituto Nacional de Investigaciones Nucleares, La Marquesa, Mexico

    Jaime Klapp

  3. CINVESTAV-IPN, Mexico City, Mexico

    Isidoro Gitler

  4. CICESE, Ensenada, Mexico

    Andrei Tchernykh

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Valdez, S.I., Trujillo-Romero, F. (2019). A Parallelized Iterative Closest Point Algorithm for 3D View Fusion. In: Torres, M., Klapp, J., Gitler, I., Tchernykh, A. (eds) Supercomputing. ISUM 2018. Communications in Computer and Information Science, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-10448-1_5

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  • DOI: https://doi.org/10.1007/978-3-030-10448-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-10447-4

  • Online ISBN: 978-3-030-10448-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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