Dismount Tracking in Urban Scenes

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0173
Agency Tracking Number: 08SB2-0515
Amount: $98,987.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: SB082-027
Solicitation Number: 2008.2
Small Business Information
11600 Sunrise Valley Drive, Suite # 290, Reston, VA, 20191
DUNS: 038732173
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Khurram Hassan-Shafique
 Principal Investigator
 (703) 654-9300
Business Contact
 Paul Brewer
Title: VP, New Technology
Phone: (703) 654-9314
Email: pbrewer@objectvideo.com
Research Institution
This SBIR Phase I project will demonstrate the feasibility and effectiveness of novel statistical models and deferred inference based techniques for robust detection and tracking of small targets in low spatial-resolution and frame-rate aerial videos. The key innovations in this effort include i) Bernoulli variable based statistical target detection framework that detects small targets by jointly modeling spatio-temporal properties of scene background and sensor geometry, ii) efficient multi-frame multi-target tracking algorithm that explicitly models common dismount tracking scenarios such as, track initiations and terminations, occlusions, target interactions, grouping behaviors, and noisy detections in a single optimization framework, and iii) forensic analysis system that enables the analysts to nominate a target of interest and efficiently determine its trajectory, the targets and objects that it interacts with, the trajectories of interacting targets, and the locations and times of interactions. The project will also benefit from ObjectVideo’s ongoing research activities on context based reasoning for false alarm reduction, context extraction, parallax modeling, and target detection in compressed aerial videos. The Phase I effort will include: development of proposed detection and tracking algorithms to enable the proposed forensic analysis system, demonstration of proof of concept, and quantitative evaluation of the proposed technologies.

* information listed above is at the time of submission.

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