Video Analysis and Dynamic Event Recognition (VADER) Engine

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0471
Agency Tracking Number: 08SB2-0419
Amount: $98,999.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: SB082-023
Solicitation Number: 2008.2
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street, Suite 400, Arlington, VA, 22202
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Bruce Swett
 Senior Scientist/Engineer
 (703) 414-5098
 bruce.swett@dac.us
Business Contact
 Kelly McClelland
Title: Director, Corporate Business Office
Phone: (703) 414-5024
Email: kelly.mcclelland@dac.us
Research Institution
N/A
Abstract
The proliferation of the battlefield with UAVs and stationary cameras has created a virtual mountain of video data. Some of that data gets analyzed thoroughly, but most does not. It is simply archived away. Buried within this mountain of video data is a virtual treasure trove of valuable intelligence that currently cannot be easily retrieved. New, advanced wide area sensors and the increasing deployment of UAVs and ground-based cameras are accelerating the growth of our archives, causing more and more of this valuable intelligence to go unutilized. The key to providing a robust video search capability is in the ability to accurately represent the content of the video in a compact, meaningful form that can be understood both by analysts and the software algorithms that will be used for rapid search and comparison. This requires both the ability to massively reduce the dimensionality of the content and the ability to represent it in a format that supports rapid search. To meet this challenge, DECISIVE ANALYTICS Corporation will leverage our on-going research in video exploitation algorithms and probabilistic relationship modeling to augment a cutting edge video pattern recognition technique to address the challenges associated with a content-based video query paradigm.

* information listed above is at the time of submission.

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