You are here
HASLOC: Hierarchical And-Or Structures for Localization and Object Recognition
Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8651-19-C-0122
Agency Tracking Number: F18A-014-0124
Amount:
$750,000.00
Phase:
Phase II
Program:
STTR
Solicitation Topic Code:
AF18A-T014
Solicitation Number:
18.A
Timeline
Solicitation Year:
2018
Award Year:
2019
Award Start Date (Proposal Award Date):
2019-06-20
Award End Date (Contract End Date):
2021-06-20
Small Business Information
15400 Calhoun Drive
Suite 190
Rockville, MD
20855
United States
DUNS:
161911532
HUBZone Owned:
No
Woman Owned:
Yes
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Naresh Cuntoor
Title: Senior Research Scientist
Phone: (301) 294-4768
Email: ncuntoor@i-a-i.com
Title: Senior Research Scientist
Phone: (301) 294-4768
Email: ncuntoor@i-a-i.com
Business Contact
Name: Mark James
Phone: (301) 294-5200
Email: mjames@i-a-i.com
Phone: (301) 294-5200
Email: mjames@i-a-i.com
Research Institution
Name: North Carolina State University
Contact: Prof. Tianfu Wu Prof. Tianfu Wu
Address:
Phone: (919) 515-2336
Type: Nonprofit College or University
Contact: Prof. Tianfu Wu Prof. Tianfu Wu
Address:
890 Oval Drive
3114 Engineering Building II
Raleigh, NC
27606
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.
* Information listed above is at the time of submission. *
