Automated Entity Classification in Video Using Soft Biometrics

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-08-M-0194
Agency Tracking Number: N081-077-0647
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2008
Solicitation Year: 2008
Solicitation Topic Code: N08-077
Solicitation Number: 2008.1
Small Business Information
PO Box 5266, Riverside, CA, 92517
DUNS: 960774941
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Agenor Mafra-Neto
 (951) 686-5008
Business Contact
 Annlok Yap
Title: Business Director
Phone: (951) 686-5008
Research Institution
In this SBIR project we will develop an automated capability to quickly recognize and classify subjects in video imagery using soft biometrics. The system will have capability to translate video streams into probabilistic biometric metadata about the observed subjects (i.e. “With 82% confidence, subject is John Smith”). We intend to address both the accuracy and speed issues to produce a simple, intuitive and maintainable/upgradeable system which will allow real time and accurate searches of massive biometric archives. In essence our solutions will work by approximating the entire dataset in a small index which can be kept in main memory. At query time, this index is searched in milliseconds for an approximate answer, which is then confirmed by loading a small fraction of the original data from disk. A crucial observation is that if the index approximation has certain properties (the lower bounding lemma) we can guarantee that the result is the same one we would have gotten if we had done the slower brute force search. This system will allow for translation of descriptions of a person to a soft biometric metadata representation, allowing distributed and (possibly disparate) imagers to collaborate in inferring matches.

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

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