Physics-based and human-derived information fusion for analysts

Erik Blasch; James Nagy; Steve Scott; Joshua Okoth; Michael Hinman

doi:10.1117/12.2264687

4 May 2017 Physics-based and human-derived information fusion for analysts

Erik Blasch, James Nagy, Steve Scott, Joshua Okoth, Michael Hinman

Proceedings Volume 10207, Next-Generation Analyst V; 1020706 (2017) https://doi.org/10.1117/12.2264687
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Recent trends in physics-based and human-derived information fusion (PHIF) have amplified the capabilities of analysts; however with the big data opportunities there is a need for open architecture designs, methods of distributed team collaboration, and visualizations. In this paper, we explore recent trends in the information fusion to support user interaction and machine analytics. Challenging scenarios requiring PHIF include combing physics-based video data with human-derived text data for enhanced simultaneous tracking and identification. A driving effort would be to provide analysts with applications, tools, and interfaces that afford effective and affordable solutions for timely decision making. Fusion at scale should be developed to allow analysts to access data, call analytics routines, enter solutions, update models, and store results for distributed decision making.

Citation Download Citation

Erik Blasch, James Nagy, Steve Scott, Joshua Okoth, and Michael Hinman "Physics-based and human-derived information fusion for analysts", Proc. SPIE 10207, Next-Generation Analyst V, 1020706 (4 May 2017); https://doi.org/10.1117/12.2264687

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