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Spotter: Exploiting Large-Format Imagery via Foveated Visual Search

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-08-M-1350
Agency Tracking Number: F073-076-0918
Amount: $99,994.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF073-076
Solicitation Number: 2007.3
Solicitation Year: 2007
Award Year: 2008
Award Start Date (Proposal Award Date): 2008-02-11
Award End Date (Contract End Date): 2008-11-30
Small Business Information
4515 Seton Center Parkway Suite 320
Austin, TX 78759
United States
DUNS: 158034665
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Thayne Coffman
 Principal Scientist
 (512) 342-0010
Business Contact
 Irene Williams
Title: COO
Phone: (512) 342-0010
Research Institution

The proposed Spotter effort develops the algorithms necessary to exploit large format (LF) imagery in an operational environment with layered sensor platforms by cueing high-resolution sensors in order to reduce downstream data volume. In order to support analysts conducting intelligence, surveillance, and reconnaissance missions, image exploitation workstations must have automatic target recognition algorithms (ATR) suitable for LF sensor data which can cue close-in sensor platforms. Spotter addresses this technical challenge by developing a suite of ATR algorithms designed for LF image sources, methods to register and fuse the outputs of these algorithms, and a cueing strategy based on efficient platform tasking. We propose a suite of algorithms inspired by our work in foveated vision systems and ongoing research in human visual search. Spotter will combine ATR results using a method modeled after the top-down theory of human gaze selection. We will quantify the sensitivity of the Spotter approach to variations in LF sensor and platform configuration. Based on our sensitivity study, we will survey available LF imagery and identify sensors for which Spotter is a feasible approach. The Spotter effort builds on a large body of our existing work in innovative techniques for foveated vision and sensor tasking.

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

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