Literature DB >> 33816956

4D street view: a video-based visualization method.

Akira Kageyama1, Naohisa Sakamoto1.   

Abstract

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.
© 2020 Kageyama and Sakamoto.

Entities:  

Keywords:  Computer simulation; High performance computing; In situ visualization; Interactive exploration of video dataset; Multi-viewpoint visualization; New method for visualization of supercomputer simulations; Omnidirectional visualization; Scientific visualization; Video-based visualization

Year:  2020        PMID: 33816956      PMCID: PMC7924531          DOI: 10.7717/peerj-cs.305

Source DB:  PubMed          Journal:  PeerJ Comput Sci        ISSN: 2376-5992


  5 in total

1.  Patterns in spherical Rayleigh-Bénard convection: a giant spiral roll and its dislocations.

Authors:  Pu Zhang; Xinhao Liao; Keke Zhang
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-11-21

2.  In situ visualization for large-scale combustion simulations.

Authors:  Hongfeng Yu; Chaoli Wang; Ray W Grout; Jacqueline H Chen; Kwan-Liu Ma
Journal:  IEEE Comput Graph Appl       Date:  2010 May-Jun       Impact factor: 2.088

3.  Visualization by proxy: a novel framework for deferred interaction with volume data.

Authors:  Anna Tikhonova; Carlos D Correa; Kwan-Liu Ma
Journal:  IEEE Trans Vis Comput Graph       Date:  2010 Nov-Dec       Impact factor: 4.579

4.  OSPRay - A CPU Ray Tracing Framework for Scientific Visualization.

Authors:  I Wald; G P Johnson; J Amstutz; C Brownlee; A Knoll; J Jeffers; J Gunther; P Navratil
Journal:  IEEE Trans Vis Comput Graph       Date:  2017-01       Impact factor: 4.579

5.  In situ visualization at extreme scale: challenges and opportunities.

Authors: 
Journal:  IEEE Comput Graph Appl       Date:  2009 Nov-Dec       Impact factor: 2.088

  5 in total

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