VISION: Video Identification of Structures, Intentions, Objects, and Networks

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0150
Agency Tracking Number: 08SB2-0391
Amount: $99,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2008
Solicitation Year: 2008
Solicitation Topic Code: SB082-021
Solicitation Number: 2008.2
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, 01801
DUNS: 967259946
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Georgiy Levchuk
 Principal Engineer
 (781) 496-2467
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Research Institution
Decision support tools for target identification and alert generation depend upon the classification of static and moving objects. Existing methods for object classification rely primarily on static information available in single-frame images. The data from long-range video surveillance assets are usually not sufficient to distinguish the objects from one another, and even if high-resolution data were available, the visual features alone would not allow determination of the intent or purpose of the objects that are of high interest to military intelligence analysis. Persistent video surveillance is a source of motion and temporal activity data that promises to enable automated object intent classification. Aptima proposes to develop the VISION decision support system to automatically recognize the intents and functions of potentially interdependent static and moving objects. The data currently acquired by video exploitation technologies (object detection, tracking and motion analysis, for example) will be inputs to VISION. VISION technology is based on high-performance empirically validated probabilistic vision-based activity recognition and temporal-relational pattern matching algorithms developed by the Aptima Team.

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

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