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US Army soldier uses a biometrics camera to capture iris biometrics data on workers at a forward operating base in northern Baghdad.

Information on U.S. Army-Managed, Portable Biometrics Data Collection Systems

Defense Systems Information Analysis Center (DSIAC) staff contacted the U.S. Army Program Executive Office for Intelligence, Electronic Warfare & Sensors (PEO IEW&S), who is responsible for developing and managing the Army’s portfolio of biometrics sensing…

Air-to-Ground Target Detection and Identification

  The Defense Systems Information Analysis Center (DSIAC) received a technical inquiry requesting information on new sensing technologies, methodologies, and algorithms for air-to-ground target tracking. DSIAC staff and subject matter experts (SMEs) reviewed publicly available…

Determining Human Identity from Motion Patterns

This inquiry stemmed from an interest in the posted article “Learning Human Identity from Motion Patterns”. A DSIAC subject matter expert from the Georgia Technical Research Institute (GTRI) performed open source searches for reports and…


Liveness Detection Can Help Defense and Other Agencies Improve Detection and Tracking of Threat Personnel

Liveness detection using techniques such as eye or lip movement analysis is a detection/sensing/security feature that can ensure biological identifiers are from the proper user or target of interest and not from someone else. As biometric authentication slowly becomes incorporated into security and law enforcement applications, increasing attention has been paid to the quality and

DOD Builds Jetson Laser Vibrometry System to ID Remote Subjects by Heartbeat

The Jetson prototype can pick up on a unique cardiac signature from 200 meters away, even through clothes. Everyone’s heart is different. Like the iris or fingerprint, our unique cardiac signature can be used as a way to tell us apart. Crucially, it can be done from a distance. It’s that last point that has

Dataset – IBM Diversity in Faces

The Diversity in Faces (DiF) is a large and diverse dataset that seeks to advance the study of fairness and accuracy in facial recognition technology.The first of its kind available to the global research community, DiF provides a dataset of annotations of one million human facial images. How do we measure and ensure diversity for