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HASLOC: Hierarchical And-Or Structures forLocalization and Object Recognition
Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8651-18-P-0057
Agency Tracking Number: F18A-014-0124
Amount:
$150,000.00
Phase:
Phase I
Program:
STTR
Solicitation Topic Code:
AF18A-T014
Solicitation Number:
2018.0
Timeline
Solicitation Year:
2018
Award Year:
2018
Award Start Date (Proposal Award Date):
2018-08-09
Award End Date (Contract End Date):
2019-08-09
Small Business Information
15400 Calhoun Drive
Rockville, MD
20855
United States
DUNS:
161911532
HUBZone Owned:
No
Woman Owned:
Yes
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Dr. Naresh Cuntoor
Phone: (301) 294-4768
Email: ncuntoor@i-a-i.com
Phone: (301) 294-4768
Email: ncuntoor@i-a-i.com
Business Contact
Name: Mark James
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
Name: Prof. Tianfu Wu
Contact: Prof. Tianfu Wu
Address:
Phone: (919) 515-2336
Type: Nonprofit College or University
Contact: Prof. Tianfu Wu
Address:
530-24 Venture II Building, Campus Box 7911
North Carolina State Univ, NC
27695
United States
Phone: (919) 515-2336
Type: Nonprofit College or University
Abstract
Target detection and recognition is a challenging problem because of changes in appearance, viewing direction, occlusion and other covariates. Systems that can accurately and efficiently detect and track objects can provide several benefits in surveillance, monitoring and other applications. As part of this effort, we propose to develop a robust learning-based approach to detect, track and recognize targets. Our approach will use a multi-layered, hierarchical model that can handle changes in target's signature and apparent view. Initially the effort will focus on EO/IR image sequences and extend the approach to multispectral data in Phase II.
* Information listed above is at the time of submission. *