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Proceedings Paper

Unusual activity detection for persistent target surveillance
Author(s): Zhihai He
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Paper Abstract

The information generated by the integrated sensor suite is massive. Simply bringing the information to the decision makers is a cognitive disaster due to the information overload. Intelligent algorithms need to be developed to exploit and filter the information. In this work, we seek to develop content-level change detection and activity-level information fusion and filtering algorithms to detect unusual activities for persistent target surveillance applications.

Paper Details

Date Published: 20 May 2005
PDF: 8 pages
Proc. SPIE 5778, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV, (20 May 2005); doi: 10.1117/12.602347
Show Author Affiliations
Zhihai He, Univ. of Missouri/Columbia (United States)


Published in SPIE Proceedings Vol. 5778:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV
Edward M. Carapezza, Editor(s)

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