Improving the Fusion Process Using Semantic Level Whole-Brain Analysis
David L. Hall, M. D. McNeese, Eileen Rotthoff, Tim Shaw, James Z. Wang
The Pennsylvania State University
Abstract:
Extensive research in the fusion community has
focused on developing techniques for level 1 fusion.
The bulk of the literature on multisensor data fusion
focuses on the automation of target tracking and
automatic target recognition. While such research is
needed, current problems involve complexities such
as identifying and tracking individual people and
groups of people, monitoring global activities and
recognition of events that may be a precursor to
terrorist activities. The requisite data for this
analysis involves sensor data (including signals,
images, and vector quantities), textual information
(from web sites and human reports), and utilization of
models. This analysis process is very human
intensive, requiring teams of analysts to search for
data, interpret the results, develop alternative
hypotheses, and assessment of the consequences of
such hypotheses.
This paper describes the development of a set of tools
aimed at level-5 fusion to support whole-brain
analysis. The toolkit encourages analysts to use and
integrate both their visual intelligence and their
language processing ability. We have developed a
set of tools to support multi-INT analysts including
tools for; (1) automated semantic labeling of images,
(2) collaboration tools, (3) cognitive aids, (4)
advanced visualization aids, and (5) context-based
interpretation techniques. These tools are being
implemented in an open architecture involving a
commercial off the shelf geographical information
system (GIS). In addition to the tool kit, a living
laboratory environment has been developed to allow
the quantitative evaluation of these aids in a
repeatable, experimental environment.
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Citation:
David L. Hall, M.D. McNeese, Eileen Rotthoff, Tim Shaw, and James
Z. Wang, ``Improving the Fusion Process Using Semantic Level
Whole-Brain Analysis,'' Proc. MSS National Symposium on Sensors and
Data Fusion, 7 pages, Monterey, CA, May 2005.
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Last Modified:
Mon Jul 18 15:41:24 EDT 2005
© 2005, James Z. Wang