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TelEOSARus Returns: Diving Deeper with EO and SAR in TeleSculptor

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-22-C-1009
Agency Tracking Number: F2D-3145
Amount: $749,999.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: AF212-D007
Solicitation Number: 21.2
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-03-16
Award End Date (Contract End Date): 2024-03-16
Small Business Information
1712 Route 9 Suite 300
Clifton Park, NY 12065-3104
United States
DUNS: 010926207
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Chet Nieter
 (919) 869-8876
Business Contact
 Ashley Carbino
Phone: (518) 836-2173
Research Institution

Current 3D reconstruction techniques from both SAR and EO sensors rely on observing a region of interest from a full 360 degree orbit, with an additional requirement for SAR reconstructions that the data collected come from multiple passes at different altitudes. These requirements are not feasible in a military operational scenario. There exists a need for methods to generate 3D models of both scenes and individual targets where the data is collected from a limited viewpoint. Kitware and Ohio State University propose to develop novel algorithms that will fuse data from both EO and SAR sensors from limited viewpoints by applying deep learning to train algorithms that will leverage the advantages of both sensor modalities and use prior knowledge to reconstruct portions of the scene that were not observed due to the limited viewpoint. These new algorithms will be incorporated into the open source TeleSculptor photogrammetry application, providing a quick transition of these new capabilities to operational use.

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

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