A point-based rendering application with a high-speed spatial interpolation

Masafumi Nakagawa, Satoshi Kuramochi, Anna Nakanishi, Yuta Sugaya

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

2 Citations (Scopus)

Abstract

Accurate 3-D scanning techniques are used for various applications. However, a viewpoint translation in point-cloud rendering reduces the visualization quality because of noticeable occlusion exposure and a noticeably uneven point distribution. In addition, recent increases in scanning speed and scanning data volume require a large video memory and high-frequency CPU. Therefore, we have developed a point-based rendering application with a high-speed spatial interpolation using a point cloud to generate virtual reality (VR) data called LiDAR VR. We have focused on the following features. First, panorama imagery can be generated automatically from arbitrary viewpoints from one observation data set. Second, it is possible that a spatial interpolation with rendering results can reduce the processing task. These features have been verified using case studies.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages1571-1574
Number of pages4
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan, Province of China
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume3

Conference

Conference32nd Asian Conference on Remote Sensing 2011, ACRS 2011
CountryTaiwan, Province of China
CityTapei
Period11/10/311/10/7

Keywords

  • LiDAR
  • Panorama imagery
  • Point cloud
  • Point-based rendering
  • Terrestrial 3D mapping
  • VR

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Nakagawa, M., Kuramochi, S., Nakanishi, A., & Sugaya, Y. (2011). A point-based rendering application with a high-speed spatial interpolation. In 32nd Asian Conference on Remote Sensing 2011, ACRS 2011 (pp. 1571-1574). (32nd Asian Conference on Remote Sensing 2011, ACRS 2011; Vol. 3).