SITIS Archives - Topic Details
Program:  SBIR
Topic Num:  A10-104 (Army)
Title:  Human Signature Collection and Exploitation via Stand-Off Non-Cooperative Sensing
Research & Technical Areas:  Sensors, Electronics, Human Systems

Acquisition Program:  PM Future Combat Systems Brigade Combat Team
  Objective:  The objective of this topic is to develop technologies which will support the sensing, processing, analysis and exploitation of signature data based upon one or more intrinsic physical and/or behavioral traits of human beings for determination of hostile intent or stress in and positive identification of human beings, at reasonable stand-off distances and capable of day or night operation.
  Description:  The Human Signature Collection and Exploitation (HSC&E) mission area has application across all branches of DoD and the Army. It includes but goes well beyond traditional cooperative Biometrics, which has as its appropriately all-consuming mission the verification of identity of individuals for such applications as access control or forensics. HSC&E responds to the challenge of warfare among the people, where combatants are mixed in with civilians. Current tactical missions must deal with non-cooperative subjects at stand-off, detecting humans in clutter, recognizing them as having been seen before or belong to recognized social groups and what activities they are performing and whether these are benign or threat behaviors, characterizing them as to their health and well-being, emotional state or intent, identifying them by association with existent data bases, and tracking them individually but also as elements of more complex group activities and motion. It is essential to be able to discriminate between enemy combatants and neutrals/friendlies. The primary purpose of this effort is to develop passive sensor technology for the determination of hostile intent or stress in human beings, at reasonable stand-off distances and capable of day or night operation, and that also affords robust positive identification. Technology Challenges - Development of passive sensors for the overt and/or covert collection of human signature phenomenology in any part of the electromagnetic or field strength spectrum. These sensors are to be designed and configured to collect these signatures at ranges and in environments appropriate to human activity such as urban and rural environments or in the areas surrounding forward operating bases. They must be designed and configured with the need for affordability foremost. Development of data reduction and information discovery tools, such as but certainly not limited non-linear dimensional reduction algorithms and optical flow analysis.

  PHASE I: The goals of Phase I are to: - Develop the plan for the complete multiphase effort; - Select candidate sensor technology. - Select candidate human signature feature vector for hostile intent/stress, including associated metrics. - Select candidate feature vector for identification, including associated metrics. - Model and demonstrate initial extraction of the above feature vectors from a multi-person data set. Data set not required to be collected under Phase I if publicly available or already a company asset. - Model the performance of the candidate sensor as a function of range up to 100 meters, and ambient illumination (must be capable of day/night operation). - Generate candidate matching template on the basis of the selected feature vectors. - Provide detailed report on Phase I effort.
  PHASE II: The goals of Phase II are to: - Design, build, and demonstrate the performance of the sensor system. - Design, build, and demonstrate the software required to extract the feature vectors. - Design, build, and demonstrate the software necessary to generate the matching template. - Design, build, and demonstrate sensor fusion structures, data reduction and information discovery algorithms, collection, processing, or fusion enabling technologies to enable near real time operation. - Integrate sensor system and software. - Collect a multi-person data set with sensor system. - Demonstrate determination of hostile intent/stress. Generate associated receiver operation characteristic (ROC) curves. - Demonstrate determination of identification. Generate associated receiver operation characteristic (ROC) curves. - Deliver operational sensor and software. - Provide detailed report on Phase II.

  PHASE III: The goals of Phase III are to: - Mature the technical design for field demonstration. - Design and implement interface with Army Intel Enterprise-compliant Biometrics Enabled Intelligence (BEI) framework being developed under CERDEC ATO(R) Biometrics – Non-Cooperatively Obtained Data and Exploitation (Bio-NODE). - Collect a multi-person data set with mature system, at ranges that exceed 30 meters and under both day and night operation. - Demonstrate determination of hostile intent/stress. Generate associated receiver operation characteristic (ROC) curves. - Demonstrate determination of identification. Generate associated receiver operation characteristic (ROC) curves. - Deliver operational sensor and software. - Provide detailed report on Phase III. Compliance and interface with ATO(R) Bio-NODE will enable transition to PM DCGS-A, JPI ICDT and PM Biometrics. Dual use includes application to challenges as are being addressed under the DHS FAST and the IARPA BEST programs and stress mitigation studies under Army Medical Research and Materiel Command, G3/5/7.

  References:  ntony, R.T. and Karakowski, J.A., 2008, “First-Principle Approach to Functionally Decomposing the JDL Fusion Model: Emphasis on Soft Target Data,” Proc. 11th Internat. Conf. Information Fusion, IEEE. Atran, S., 2008a, Who Becomes a Terrorist Today, Perspectives on Terrorism, Vol. II, Issue 5. Atran, S., 2008b, The Making a Terrorist: A Need for Understanding from the Field. Testimony before the House Appropriations Subcommittee on Homeland Security, Washington, DC, March 12, 2008. Blechko, A., Darker, I.T., Gale, A.G., 2009, The Role of Emotion Recognition from Non-Verbal Behavior in Detection of Concealed Firearm Carrying, Proc. Human Factors and Ergonomics Soc. 53rd Annual Meeting-2009, 1363–1367. Bossé, E., Roy, J., and Wark, S., 2007, Concepts, Models, and Tools for Information Fusion, ARTech House, Boston. Diego A. Socolinsky, Andrea Selinger and Joshua D. Neuheisel, 2003, “Face recognition with visible and thermal infrared imagery,” Computer Vision and Image Understanding, Volume 91, Issues 1-2, July-August 2003, Pages 72-114,Special Issue on Face Recognition DTIC Search Engine: http://www.dtic.mil/ Ekman, P., and Friesen, W., 1978, Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto, 1978. See also http://en.wikipedia.org/wiki/Facial_Action_Coding_System. Jones, F. and Bright, J., 2001, Stress: Myth, Theory and Research, Prentice Hall Kulic, D. and Croft, D. 2005, “Anxiety detection during human robot interaction,” Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), pp. 616-621. SENSIAC Military Sensing Information Analysis Center: http://www.sensiac.gatech.edu/ SPIE - Conferences & Publications on Photonics, Optics, & Imaging: http://www.spie.org/ Steinberg, A.N., Bowman, C.L., and White, F.E., 1999, “Revisions to the JDL Model”, Joint NATO/IRIS Conference Proceedings, Quebec, October, 1998 and Sensor Fusion: Architectures, Algorithms, and Applications, Proceedings of the SPIE, Vol. 3719. US Army Night Vision and Electronic Sensors Directorate http//www.nvl.army.mil/index_main.php/

Keywords:  sensors, human signatures, biometrics, algorithms, EO/IR, RF, modeling, facial recognition

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