A System to Analyze Facial Features to Enable Operator Condition Tracking (AFFECT)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-11-C-0030
Agency Tracking Number: A2-4087
Amount: $749,750.00
Phase: Phase II
Program: STTR
Awards Year: 2011
Solicitation Year: 2009
Solicitation Topic Code: A09A-T006
Solicitation Number: 2009.A
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, -
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Camille Monnier
 Senior Scientist
 (617) 461-0488
 cmonnier@cra.com
Business Contact
 Ninos Hanna
Title: Contract Specialist
Phone: (617) 461-0488
Email: nhanna@cra.com
Research Institution
 University at Buffalo, SUNY
 Martina Tsai
 Sponsored Projects Services
402 Crofts Hall
Buffalo, NY, 14260-7016
 (716) 645-4421
 Nonprofit college or university
Abstract
Modern military and security scenarios increasingly demand rapid evaluation of human affective states, accurately detecting stress, anxiety, uncertainty, and fatigue (SAUF) to assess warfighter effectiveness or to advance security screening and interrogation objectives. In our Phase I effort, we designed and demonstrated a system to Analyze Facial Features to Enable Operator Condition Tracking (AFFECT) by extracting a broad array of features from visible and thermal spectrum imagery of the human face. We designed an effective stress induction protocol and recorded the resultant elevated stress levels using heart rate variability data. We demonstrated the feasibility of our classification methodology by implementing a prototype of the AFFECT system. For Phase II, we propose to expand on these results by designing new affective induction techniques and ground-truth metrics for anxiety, uncertainty, and fatigue. We will detect these states by applying novel visual and thermal feature extraction algorithms, and by implementing the temporal feature algorithms designed in Phase I. We are confident that the sound principles underlying our Phase I approach will provide a robust foundation for expanded SAUF classification in Phase II.

* information listed above is at the time of submission.

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