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Learning Models for Predictive Behavioral Intent and Activity Analysis in Wide Area Video Surveillance

Award Information

Award #
Awardee County
Congressional District
Funding First Awarded
Total funding (to date)

Description of original award (Fiscal Year 2009, $271,516)

This award will provide funding for the University of Houston to develop software tools to enable the tracking of an individual across surveillance video from cameras with non-overlapping fields of view over a wide area. Wide area surveillance is one of the highest priority law enforcement technology needs, and this technology will improve the situational awareness of state and local law enforcement officers.


This project will continue development of an intelligent, non-obtrusive, real-time, continuous monitoring system for assessing activity and predicting emergent suspicious and criminal behavior across a network of distributed cameras.

This award was made competitively under the NIJ 2009 "Technology Research and Development for Law Enforcement and Corrections Application" solicitation. The goal of this effort is to develop software tools to enable the tracking of an individual across surveillance videos originating from CCTV cameras with non-overlapping fields of view in a wide area. Research to date shows that CCTV systems can have a positive effect on crime and prevention, but the effect is modest or inconsistent depending on a number of factors. This effort, and related research and development efforts, is intended to foster development of smart CCTV systems that will overcome these inhibiting factors. This award has been funded incrementally. This is the third and final supplement needed to complete the effort initially proposed by the University of Houston. nca/ncf

Date Created: September 23, 2009