2020年
4D street view: a video-based visualization method.
PeerJ Comput. Sci.
- ,
- 巻
- 6
- 号
- 開始ページ
- e305
- 終了ページ
- 305
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.7717/peerj-cs.305
- 出版者・発行元
- PEERJ INC
We propose a new visualization method for massive supercomputer simulations. The key idea is to scatter multiple omnidirectional cameras to record the simulation via in situ visualization. After the simulations are complete, researchers can interactively explore the data collection of the recorded videos by navigating along a path in four-dimensional spacetime. We demonstrate the feasibility of this method by applying it to three different fluid and magnetohydrodynamics simulations using up to 1,000 omnidirectional cameras.
- リンク情報
-
- DOI
- https://doi.org/10.7717/peerj-cs.305
- DBLP
- https://dblp.uni-trier.de/rec/journals/peerj-cs/KageyamaS20
- CiNii Research
- https://cir.nii.ac.jp/crid/1050294045368932736?lang=ja
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000589779300001&DestApp=WOS_CPL
- URL
- https://dblp.uni-trier.de/db/journals/peerj-cs/peerj-cs6.html#KageyamaS20
- ID情報
-
- DOI : 10.7717/peerj-cs.305
- eISSN : 2376-5992
- DBLP ID : journals/peerj-cs/KageyamaS20
- CiNii Articles ID : 120006919977
- CiNii Research ID : 1050294045368932736
- ORCIDのPut Code : 83111631
- Web of Science ID : WOS:000589779300001