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Proceedings Paper

Visualization of graphical information fusion results
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Paper Abstract

Graphical fusion methods are popular to describe distributed sensor applications such as target tracking and pattern recognition. Additional graphical methods include network analysis for social, communications, and sensor management. With the growing availability of various data modalities, graphical fusion methods are widely used to combine data from multiple sensors and modalities. To better understand the usefulness of graph fusion approaches, we address visualization to increase user comprehension of multi-modal data. The paper demonstrates a use case that combines graphs from text reports and target tracks to associate events and activities of interest visualization for testing Measures of Performance (MOP) and Measures of Effectiveness (MOE). The analysis includes the presentation of the separate graphs and then graph-fusion visualization for linking network graphs for tracking and classification.

Paper Details

Date Published: 20 June 2014
PDF: 10 pages
Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90910L (20 June 2014); doi: 10.1117/12.2052892
Show Author Affiliations
Erik Blasch, Air Force Research Lab. (United States)
Georgiy Levchuk, Aptima, Inc. (United States)
Gennady Staskevich, Air Force Research Lab. (United States)
Dustin Burke, Aptima, Inc. (United States)
Alex Aved, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 9091:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
Ivan Kadar, Editor(s)

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