Evaluation of projection model for random point cloud

Konosuke Kataoka, Masafumi Nakagawa

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies
出版社Asian Association on Remote Sensing
出版ステータスPublished - 2014
イベント35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 - Nay Pyi Taw, Myanmar
継続期間: 2014 10 272014 10 31

Other

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

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信

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