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DigitalTripwire - A Small, Automated Human-Detection System

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-07-C-0280
Agency Tracking Number: 07ST1-0094
Amount: $98,997.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: ST071-009
Solicitation Number: N/A
Timeline
Solicitation Year: 2007
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-08-15
Award End Date (Contract End Date): 2008-08-29
Small Business Information
6825 Pine Street, Suite 141
Omaha, NE 68106
United States
DUNS: 949183701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Kevin Blenkhorn
 Director
 (703) 236-6993
 kevin.blenkhorn@21csi.com
Business Contact
 Stuart Aldridge
Title: Deputy CTO
Phone: (402) 505-7887
Email: stuart@21csi.com
Research Institution
 MISSOURI STATE UNIV.
 James P Baker
 
901 South National Avenue
Springfield, MO 65897
United States

 (417) 836-5972
 Nonprofit College or University
Abstract

We currently have thousands of security cameras in the war zone. Automated Target Recognition (ATR) is essential for reducing the manpower required for monitoring the security cameras. Having human operators staring at video screens for hours at a time is not an effective use of our forces. ATR is a terrific force-multiplier since it reduces the number of security personnel required to monitor surveillance systems. A combined system with software-agents monitoring multiple cameras, backed up by a small number of security personnel will make a very powerful system, with minimal false-negatives or false-positives. The team of 21st Century Systems Incorporated and Missouri State University is pleased to propose to research and develop our DigitalTripwire concept. The DigitalTripwire system is a small, self-contained sensor that can operate unattended for weeks or months on battery power. It is intended to augment security operations by providing persistent surveillance for the area in the camera's field of view. The device itself consists of a small single-board computer connected to a video camera and a wireless network interface. The heart of the system is computer vision software that analyses the video stream from the camera and classifies objects into categories.

* Information listed above is at the time of submission. *

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