Advertisement

Development of a Scanning Support System Using Augmented Reality for 3D Environment Model Reconstruction

  • Yuki Harazono
  • Hirotake Ishii
  • Hiroshi Shimoda
  • Yuya Kouda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 903)

Abstract

3D reconstruction models are useful for many situations in maintenance and decommissioning work at nuclear power plants (NPPs). There is a method to make the models from color and depth images. When using the method, it is necessary to scan a target environment without missing in order to make detailed and precise models. However, work sites at NPP are very complicated, and it is difficult to scan without missing. In this study, we aim to develop a scanning support system that enables users to make 3D reconstruction models without missing even in a very complicated environment such as NPPs. The system reminds and encourages users to scan work sites by visualizing unscanned area using an algorithm extended truncated signed distance function.

Keywords

Augmented reality Model reconstruction Environment scanning support 

References

  1. 1.
    Harazono, Y., Kimura, T., et al.: Development of an information reference system using reconstruction models of nuclear power plants. Nucl. Eng. Technol. 50(4), 606–612 (2018)CrossRefGoogle Scholar
  2. 2.
    Izadi, S., Kim, D., et al.: KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 559–568 (2011)Google Scholar
  3. 3.
    Remondino, F., Barazzetti, L., et al.: UAV photogrammetry for mapping and 3D modeling current status and future perspectives. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 25–31 (2011)CrossRefGoogle Scholar
  4. 4.
    Xiong, X., Adan, A., et al.: Automatic creation of semantically rich 3D building models from laser scanner data. Autom. Constr. 31, 325–337 (2012)CrossRefGoogle Scholar
  5. 5.
    Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 303–312 (1996)Google Scholar
  6. 6.
    Choi, S., Zhou, Q., Koltun, V.: Augmented ICL-NUIM Dataset. http://redwood-data.org/indoor/dataset.html. Accessed 15 Oct 2018

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yuki Harazono
    • 1
  • Hirotake Ishii
    • 1
  • Hiroshi Shimoda
    • 1
  • Yuya Kouda
    • 2
  1. 1.Graduate School of Energy ScienceKyoto UniversityKyoto-ShiJapan
  2. 2.Fugen Decommissioning Engineering CenterJapan Atomic Energy AgencyTsuruga-ShiJapan

Personalised recommendations