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System for Nighttime and Low-Light Face Recognition

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: H9240518P0002
Agency Tracking Number: S18A-001-0010
Amount: $149,969.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: SOCOM18A-001
Solicitation Number: 2018.0
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-06-14
Award End Date (Contract End Date): 2018-12-14
Small Business Information
9104 Mistwood Drive
Potomac, MD 20854
United States
DUNS: 080329868
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Carlos Castillo
 (202) 660-3761
 carlos.castillo@mukh.com
Business Contact
 Rama Chellappa
Phone: (301) 466-1623
Email: rama.chellappa@mukh.com
Research Institution
 Carnegie Lellon University
 Ms. Heather Bragg
 
5000 Forbes Ave
Pittsburgh, PA 15213
United States

 (412) 268-2998
 Nonprofit college or university
Abstract

Recognizing faces in low-light and nighttime conditions is a challenging problem due to the noisy and poor quality nature of the images.Thermal imaging is often used to obtain facial biometric in such conditions. Thermal face images, while having a strong signature at nighttime, are not typically maintained in biometric-enabled watch lists and so must be compared with visible-light face images to enable face recognition in low lighting conditions.In this project, wea thorough feasibility study to investigate the limits of current deep learning-based cross-modal matching algorithms for visible-to-thermal matching.In particular, the goals of this project are as follows:-Collect a dataset consisting of face signatures across the spectrum from 100 subjects using the Army Research Laboratory Government Furnished Equipment (GFE).-Integrate, fine-tune and evaluate the best performing face verification and recognition system from the JANUS project on the new heterogeneous face dataset.-Design and evaluate a robust deep learning-based domain adaptive matching system (or systems) for cross-domain face recognition. Address the risks and potential payoffs of this technology

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

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