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TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories

  • Naoko Sawada
  • , Masanori Nakayama
  • , Hsiang Yun Wu
  • , Makoto Uemura
  • , Issei Fujishiro

研究成果: Conference contribution

抄録

Astronomers have been observing blazars to solve the mystery of the relativistic jet. A technique called TimeTubes uses a 3D volumetric tube to visualize the time-dependent multivariate observed datasets and allows astronomers to interactively analyze the dynamic behavior of and relationship among those variables. However, the observed datasets themselves exhibit uncertainty due to their errors and missing periods, whereas periods interpolated by TimeTubes result in a different type of uncertainty. In this paper, we present a technique for ameliorating such data-and mappinginherent uncertainties: visual fusion of datasets for the same blazar from two different observatories. Visual data fusion with Time-Tubes enables astronomers to validate the datasets in a meticulous manner.

本文言語English
ホスト出版物のタイトルCGI 2017 - Proceedings of the 2017 Computer Graphics International Conference
出版社Association for Computing Machinery
ISBN(電子版)9781450352284
DOI
出版ステータスPublished - 2017 6月 27
イベント2017 Computer Graphics International Conference, CGI 2017 - Yokohama, Japan
継続期間: 2017 6月 272017 6月 30

出版物シリーズ

名前ACM International Conference Proceeding Series
Part F128640

Other

Other2017 Computer Graphics International Conference, CGI 2017
国/地域Japan
CityYokohama
Period17/6/2717/6/30

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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