Automated night/day standoff detection, tracking, and identification of personnel for installation protection

Brian E. Lemoff; Robert B. Martin; Mikhail Sluch; Kristopher M. Kafka; William McCormick; Robert Ice

doi:10.1117/12.2016342

6 June 2013 Automated night/day standoff detection, tracking, and identification of personnel for installation protection

Brian E. Lemoff, Robert B. Martin, Mikhail Sluch, Kristopher M. Kafka, William McCormick, Robert Ice

Author Affiliations +

Proceedings Volume 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII; 87110N (2013) https://doi.org/10.1117/12.2016342
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

The capability to positively and covertly identify people at a safe distance, 24-hours per day, could provide a valuable advantage in protecting installations, both domestically and in an asymmetric warfare environment. This capability would enable installation security officers to identify known bad actors from a safe distance, even if they are approaching under cover of darkness. We will describe an active-SWIR imaging system being developed to automatically detect, track, and identify people at long range using computer face recognition. The system illuminates the target with an eye-safe and invisible SWIR laser beam, to provide consistent high-resolution imagery night and day. SWIR facial imagery produced by the system is matched against a watch-list of mug shots using computer face recognition algorithms. The current system relies on an operator to point the camera and to review and interpret the face recognition results. Automation software is being developed that will allow the system to be cued to a location by an external system, automatically detect a person, track the person as they move, zoom in on the face, select good facial images, and process the face recognition results, producing alarms and sharing data with other systems when people are detected and identified. Progress on the automation of this system will be presented along with experimental night-time face recognition results at distance.

Citation Download Citation

Brian E. Lemoff, Robert B. Martin, Mikhail Sluch, Kristopher M. Kafka, William McCormick, and Robert Ice "Automated night/day standoff detection, tracking, and identification of personnel for installation protection", Proc. SPIE 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII, 87110N (6 June 2013); https://doi.org/10.1117/12.2016342

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