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Image-based Tracking and Sensor Resource Allocation for Unmanned Aerial Vehicles

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-08-C-0038
Agency Tracking Number: F064-020-0399
Amount: $749,999.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF06-T020
Solicitation Number: N/A
Timeline
Solicitation Year: 2006
Award Year: 2008
Award Start Date (Proposal Award Date): 2007-11-16
Award End Date (Contract End Date): 2009-11-16
Small Business Information
6800 Cortona Drive
Goleta, CA 93117
United States
DUNS: 054672662
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Mahendra Mallick
 Senior Scientist
 (805) 968-6787
 mmallick@toyon.com
Business Contact
 Marcella Lindbery
Title: Director of Finance and Contracts
Phone: (805) 968-6787
Email: mlindbery@toyon.com
Research Institution
 GEORGE MASON UNIV.
 Shelby Oros
 
Office of Sponsored Programs 10517-C Braddock Rd., #2501
Fairfax, VA 22032
United States

 (703) 993-8927
 Nonprofit College or University
Abstract

A key objective of our project is to develop advanced algorithms and software to track people and vehicles in an urban environment using video imagery from multiple unmanned aerial vehicles (UAVs). Track continuity of targets of interest (TOI) is an essential requirement. Collaborative UAV trajectory planning and camera pointing to collect continuous observations on one or more TOI by a team of UAVs are required when the line-of-sight of a video camera is occluded by buildings or trees. In the Phase I, we developed advanced feature-aided video tracking algorithms and software using the multiple hypotheses tracking (MHT) approach. We used real video data and developed algorithms and software for realistic video measurement model, geolocation, track initiation, and nonlinear filtering. In Phase I, we processed real UAV video data and obtained preliminary results. In Phase II, we shall process a large number of datasets with single and multiple UAVs. We propose to develop sensor resource management algorithms and software by leveraging on an AFOSR funded project on dynamic UAV trajectory planning and camera pointing to mitigate the occlusion of the camera line-of-sight.

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

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