Context-sensitive Content Extraction and Scene Understanding

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-07-M-0287
Agency Tracking Number: N071-085-0199
Amount: $99,921.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2007
Solicitation Topic Code: N07-085
Solicitation Number: 2007.1
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
 Mun Wai Lee
 Research Scientist
 (703) 654-9300
Business Contact
 Paul Brewer
Title: VP, New Technology
Phone: (703) 654-9314
Research Institution
Over the last few decades, progress toward automatic video understanding was almost exclusively due to improvements in bottom-up image and video analysis. As was the case with the initial top-down approaches, pure bottom-up approaches have run into fundamental limits. This proposal expands on recent advances in top-down/bottom-up information fusion to exploit syntactic and semantic information inherent in both approaches. Bottom-up information describes scene elements, moving objects and their interactions. Top-down information encapsulates object- and domain-specific information. Top-down information will be represented using stochastic attribute grammars. Grammars, studied mostly in language, are known for their expressive power. Transferring the idea of a grammar from language to vision, ObjectVideo proposes to define a visual vocabulary from pixels, primitives, parts, objects and scenes, and also specify their spatio-temporal or compositional relations. A stochastic bottom-up/top-down inference strategy will use this representation for efficient and accurate content extraction. The detailed representation will be used to automatically annotate imagery specifying its content and context. At the completion of Phase I, ObjectVideo will demonstrate a proof of concept system for syntactic, semantic and conceptual content extraction from maritime and urban imagery.

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

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