Performance Modeling of Feature Aided Trackers

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$99,732.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-11-M-1123
Award Id:
n/a
Agency Tracking Number:
F103-192-2631
Solicitation Year:
2010
Solicitation Topic Code:
AF103-192
Solicitation Number:
2010.3
Small Business Information
Sheet Dynamics, Limited (Currently Etegent Technologies, LTD)
1775 Mentor Avenue, Suite 302, Cincinnati, OH, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
96-473-04
Principal Investigator:
Adam Nolan
Chief Technical Officer
(513) 631-0579
adam.nolan@etegent.com
Business Contact:
Stuart Shelley
Principle
(513) 631-0579
stuart.shelley@etegent.com
Research Institution:
Stub




Abstract
The bandwidth of current and future image analysts is insufficient to ingest the vast quantity of data generated by staring sensing platforms. Because of this, signature exploitation algorithms need to play a role in the data processing chain to cue analysts to specific regions of interest within the imagery. For systems which utilize exploitation algorithms, there is a need to understand the ability and limitations under various conditions. We propose a feature aided tracker that is able to model its performance based on the current operating conditions. This performance model is a crucial component of any layered sensing architecture. BENEFIT: EO based tracking algorithms for security applications, crowd monitoring, consumer characterization, and traffic flow analysis all suffer from limited self diagnostics. Algorithms which are able to predict performance corresponding to specific operating conditions would be able to 1)optimize sensor collection 2)mitigate false alarms 3)allow fuzzy decision making and 4)allocate additional resources when needed.

* information listed above is at the time of submission.

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