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3DWAR: 3D Wide Area Reconstruction

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0464
Agency Tracking Number: 08SB2-0524
Amount: $98,991.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SB082-028
Solicitation Number: 2008.2
Solicitation Year: 2008
Award Year: 2009
Award Start Date (Proposal Award Date): 2009-05-19
Award End Date (Contract End Date): 2010-01-14
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: CEO
Phone: (512) 342-0010
Research Institution

The 3D Wide Area Reconstruction (3DWAR) effort brings the operational benefits of superior 3D reconstructions to the warfighter. Superior performance is achieved by combining super-resolution (SR) and computational stereo processing to reconstruct 3D models of the combat environment with voxel size of one half the imagery ground sample distance. If input data has sufficient 3D visual effects to support stereo reconstruction, then those effects are also sufficient to derail any SR processing that does not explicitly account for them. We extend our multi-view Accumulation-Based Modeling (ABM) computational stereo approach to tailor it to the operational problem. ABM is naturally compatible with wide field of view and rolling shutter cameras due to its unique approaches to evidence fusion and interpretation. Phase 1 establishes the feasibility of the proposed technical approach with three spirals of theoretic and empirical analysis. Together, these spirals lay a solid foundation for Phase 2 by providing proof of concept implementations and quantitative performance analyses of the approach. Phase 2 will augment and fully develop the most promising variations, and demonstrate an integrated engineering prototype on operationally relevant imagery. The proposed work leverages our past experience in computational stereo and super-resolution, as well as our existing stereo capabilities.

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

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