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A methodology for supporting collaborative exploratory analysis of massive data sets in tele-immersive environments

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5 Author(s)
J. Leigh ; Electron. Visualization Lab., Illinois Univ., Chicago, IL, USA ; A. E. Johnson ; T. A. DeFanti ; S. Bailey
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This paper proposes a methodology for employing collaborative, immersive virtual environments as a high-end visualization interface for massive data-sets. The methodology employs feature detection, partitioning, summarization and decimation to significantly cull massive data-sets. These reduced data-sets are then distributed to the remote CAVEs, ImmersaDesks and desktop workstations for viewing. The paper also discusses novel techniques for collaborative visualization and meta-data creation

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High Performance Distributed Computing, 1999. Proceedings. The Eighth International Symposium on

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