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Proceedings Paper

Human behavior digitization and intent recognition using data modeling
Author(s): Holger M. Jaenisch; James W. Handley; Kristina L. Jaenisch; Nathaniel G. Albritton
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Paper Abstract

Autonomous and network centric smart cameras for use in homeland security and other human activities monitoring applications require a multi-layer approach for real time image processing. We propose a novel method to achieve behavior digitization and preemptive course of action (COA) analysis by converting temporal and spatial pixel subframes into a form that can be encoded into equation based Data Models. Output from these Data Models is fused with evidence and sensor data in the COA decision cascade, which recommends COAs that yield evidence. Evidence from the decision cascade continues to be amassed until the hypothesized threat forms a strong enough conviction to initiate alert responses and external intercepting events. This paper outlines our proposed methodology and approach.

Paper Details

Date Published: 30 April 2009
PDF: 12 pages
Proc. SPIE 7346, Visual Analytics for Homeland Defense and Security, 73460E (30 April 2009); doi: 10.1117/12.817769
Show Author Affiliations
Holger M. Jaenisch, Licht Strahl Engineering Inc. (United States)
Amtec Corp. (United States)
James W. Handley, Licht Strahl Engineering Inc. (United States)
Amtec Corp. (United States)
Kristina L. Jaenisch, Licht Strahl Engineering Inc. (United States)
Nathaniel G. Albritton, Amtec Corp. (United States)


Published in SPIE Proceedings Vol. 7346:
Visual Analytics for Homeland Defense and Security
William J. Tolone; William Ribarsky, Editor(s)

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