Surface modeling based on point cloud rendering using terrestrial LiDAR data

Konosuke Kataoka, Masafumi Nakagawa

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

1 Citation (Scopus)

Abstract

Point cloud data are acquired using 3D scanner, such as a terrestrial laser scanner and land-based mobile mapping systems, in a surveying, mapping, structure maintenance, and environment monitoring. The latest 3D scanners perform a rapid and massive data acquisition. However, the massive data require huge processing time in data sharing, visualization and 3D modeling. We propose a methodology to improve a performance in 3D surface modeling using point cloud data projected into a panoramic space. Thus, we have clarified that our approach can improve workability in 3D modeling. Additionally, we confirmed that acquired 3D point cloud data with terrestrial laser scanner data can be classified on 2D panoramic range image using normal vectors estimated from point cloud. This classification is based on 2D image processing. However, we also confirmed that a result from proposed modeling was equivalent to conventional 3D modeling.

Original languageEnglish
Title of host publication34th Asian Conference on Remote Sensing 2013, ACRS 2013
PublisherAsian Association on Remote Sensing
Pages1248-1253
Number of pages6
ISBN (Print)9781629939100
Publication statusPublished - 2013 Jan 1
Event34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
Duration: 2013 Oct 202013 Oct 24

Publication series

Name34th Asian Conference on Remote Sensing 2013, ACRS 2013
Volume2

Conference

Conference34th Asian Conference on Remote Sensing 2013, ACRS 2013
CountryIndonesia
CityBali
Period13/10/2013/10/24

Keywords

  • 3D modeling
  • 3D scanner
  • Multi-layered panoramic range image
  • Point cloud

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Kataoka, K., & Nakagawa, M. (2013). Surface modeling based on point cloud rendering using terrestrial LiDAR data. In 34th Asian Conference on Remote Sensing 2013, ACRS 2013 (pp. 1248-1253). (34th Asian Conference on Remote Sensing 2013, ACRS 2013; Vol. 2). Asian Association on Remote Sensing.