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Physical Optics Corporation SBIR Phase I Award, October 2020

A SBIR Phase I contract was awarded to Physical Optics Corporation in October, 2020 for $99,997.0 USD from the U.S. Department of Defense and National Geospatial-Intelligence Agency.

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Contents

sbir.gov/node/2174171
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Physical Optics Corporation
Physical Optics Corporation
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
National Geospatial-Intelligence Agency
National Geospatial-Intelligence Agency
0
Award Type
SBIR0
Contract Number (US Government)
HM047620C00830
Award Phase
Phase I0
Award Amount (USD)
99,9970
Date Awarded
October 5, 2020
0
End Date
July 4, 2021
0
Abstract

To address the NGA’s need to fully automate recovery of camera orientation parameters from ground-level imagery, Physical Optics Corporation (POC) proposes to develop new Automated Camera Orientation Recovery Software (ACORS). It is based on a new, multicue combination of algorithms for finding true horizon lines in images. Specifically, the innovation in locating occluded true horizon lines below visible skylines enables ACORS to perform fully automated extraction of camera pitch and roll angles and their uncertainties from individual images or video frames in which the skylines are already labeled. ACORS will also optionally annotate this imagery with the horizon lines it found and their error bounds. As a result, ACORS offers fully automated and accelerated recovery of camera orientations from batches of ground-based imagery, which directly addresses the NGA’s requirements. In Phase I, POC will demonstrate the feasibility of ACORS by identifying, implementing, optimizing, and evaluating a suitable combination of algorithms, reaching technology readiness level (TRL)-3. In Phase II, POC plans to develop a TRL-6 ACORS prototype supporting complete automation and rigorous error tracking. We will also assemble diverse training and testing datasets and develop performance metrics for varying operating conditions and sensor types, taking into account possible confounding factors.

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