Panoramic rendering-based polygon extraction from indoor mobile LiDAR data

M. Nakagawa, K. Kataoka, T. Yamamoto, M. Shiozaki, T. Ohhashi

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


In this paper, we propose a method for panoramic point-cloud rendering-based polygon extraction from indoor mobile LiDAR data. Our aim was to improve region-based point-cloud clustering in modeling after point-cloud registration. First, we propose a point-cloud clustering methodology for polygon extraction on a panoramic range image generated with point-based rendering from a massive point cloud. Next, we describe an experiment that was conducted to verify our methodology with an indoor mobile mapping system in an indoor environment. This experiment was wall-surface extraction using a rendered point-cloud from 64 viewpoints over a wide indoor area. Finally, we confirmed that our proposed methodology could achieve polygon extraction through point-cloud clustering from a complex indoor environment.

Original languageEnglish
Pages (from-to)181-186
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Issue number4
Publication statusPublished - 2014
EventISPRS Technical Commission IV Symposium 2014 - Suzhou, China
Duration: 2014 May 142014 May 16


  • 3D polygon extraction
  • Indoor mobile mapping
  • Point cloud clustering
  • Point-based rendering
  • Point-cloud

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development


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