Evaluation of projection model for random point cloud

Konosuke Kataoka, Masafumi Nakagawa

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

1 Citation (Scopus)

Abstract

Recently, point cloud data are acquired by some platforms, such as a terrestrial laser scanner, land-based mobile mapping system (MMS), and airborne LiDAR. These systems can achieve a rapid and massive point cloud data acquisition for road surveying, mapping, structure maintenance, and environment monitoring. However, massive point cloud data require huge processing time in data sharing, visualization and 3D modeling. Therefore, we have proposed a performance improvement of point cloud processing based on point-based rendering approach. Our point-based rendering can select several projection models, such as a spherical, cylindrical, and orthogonal model. Each model has different advantages and disadvantages. Therefore, we proposed a methodology to select a suitable projection model in some point cloud editing works in a road monitoring, structure monitoring, surveying, and indoor mapping. In this paper, we evaluated each projection models through some experiments using terrestrial LiDAR and MMS data.

Original languageEnglish
Title of host publication35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies
PublisherAsian Association on Remote Sensing
Publication statusPublished - 2014
Event35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 - Nay Pyi Taw, Myanmar
Duration: 2014 Oct 272014 Oct 31

Other

Other35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014
CountryMyanmar
CityNay Pyi Taw
Period14/10/2714/10/31

Fingerprint

Surveying
Monitoring
Processing
Data acquisition
Visualization
Lasers
Experiments

Keywords

  • Point cloud projection model
  • Point-based rendering
  • Random point cloud

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Kataoka, K., & Nakagawa, M. (2014). Evaluation of projection model for random point cloud. In 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies Asian Association on Remote Sensing.

Evaluation of projection model for random point cloud. / Kataoka, Konosuke; Nakagawa, Masafumi.

35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies. Asian Association on Remote Sensing, 2014.

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

Kataoka, K & Nakagawa, M 2014, Evaluation of projection model for random point cloud. in 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies. Asian Association on Remote Sensing, 35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014, Nay Pyi Taw, Myanmar, 14/10/27.
Kataoka K, Nakagawa M. Evaluation of projection model for random point cloud. In 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies. Asian Association on Remote Sensing. 2014
Kataoka, Konosuke ; Nakagawa, Masafumi. / Evaluation of projection model for random point cloud. 35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies. Asian Association on Remote Sensing, 2014.
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