Visualizing and Tracking Evolving Features in 3D Unstructured and Adaptive Datasets

Technical Report · Thu Aug 01 00:00:00 EDT 2002

DOI:https://doi.org/10.2172/948554· OSTI ID:948554

Silver, D ^[1]; Zabusky, N

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1. Rutgers University

The massive amounts of time-varying datasets being generated demand new visualization and quantification techniques. Visualization alone is not sufficient. Without proper measurement information/computations real science cannot be done. Our focus is this work was to combine visualization with quantification of the data to allow for advanced querying and searching. As part of this proposal, we have developed a feature extraction adn tracking methodology which allows researcher to identify features of interest and follow their evolution over time. The implementation is distributed and operates over data In-situ: where it is stored and when it was computed.

• Research Organization: Rutgers University
• Sponsoring Organization: USDOE Office of Energy Research (ER)
• DOE Contract Number: FG02-98ER25364
• OSTI ID: 948554
• Report Number(s): DOE/ER/25364-1
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
99 GENERAL AND MISCELLANEOUS
COMPUTER GRAPHICS
DATA ANALYSIS
IMPLEMENTATION
INFORMATION RETRIEVAL
Scientific Visualization
Computational Fluid Dynamics
Feature Tracking
Distributed Computing
THREE-DIMENSIONAL CALCULATIONS