Silhouette-based three dimensional image registration using CMA-ES with joint scheme of partial restart and variable fixing

Takuto Shigenobu, Takuya Ushinohama, Hiroshi Kawasaki, Satoshi Ono

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a three-dimensional (3D) entire shape reconstruction method that performs simultaneous 3D registration of multiple depth images obtained from multiple viewpoints. With the combination of a silhouette-based objective function and evolutionary computation algorithms, the proposed method realizes the entire shape reconstruction from small number (two or three) of depth images, which do not involve enough overlapping regions for other 3D registration methods. In particular, this paper proposes a CMA-ES algorithm with regional intensification techniques (CMA-ESPR+VF) to speed up the registration process. Experimental results show that the proposed CMA-ESPR+VF achieved a speedup that is at most 18 times faster than self-adaptive differential evolution.

Original languageEnglish
Title of host publicationGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages133-134
Number of pages2
ISBN (Electronic)9781450357647
DOIs
Publication statusPublished - Jul 6 2018
Event2018 Genetic and Evolutionary Computation Conference, GECCO 2018 - Kyoto, Japan
Duration: Jul 15 2018Jul 19 2018

Publication series

NameGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

Other

Other2018 Genetic and Evolutionary Computation Conference, GECCO 2018
CountryJapan
CityKyoto
Period7/15/187/19/18

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software
  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Shigenobu, T., Ushinohama, T., Kawasaki, H., & Ono, S. (2018). Silhouette-based three dimensional image registration using CMA-ES with joint scheme of partial restart and variable fixing. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion (pp. 133-134). (GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion). Association for Computing Machinery, Inc. https://doi.org/10.1145/3205651.3205791