Long-range night/day human identification using active-SWIR imaging
| Autor: | Mikhail Sluch, Brian E. Lemoff, Robert Ice, William McCormick, Robert B. Martin, Kristopher M. Kafka |
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| Rok vydání: | 2013 |
| Předmět: |
Biometrics
business.industry Computer science Near-infrared spectroscopy ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Field of view Facial recognition system Identification (information) Night vision Face (geometry) Range (statistics) Computer vision Artificial intelligence Zoom business ComputingMethodologies_COMPUTERGRAPHICS Remote sensing |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| Popis: | Positive identification of personnel from a safe distance is a long-standing need for security and defense applications. Advances in computer face recognition have made this a reliable means of identification when facial imagery of sufficient resolution is available to be matched against a database of mug shots. Long-range identification at night requires that the face be actively illuminated; however, for visible and NIR illumination, the intensity required to produce high-resolution long-range imagery typically creates an eye-safety hazard. SWIR illumination makes active- SWIR imaging a promising approach to long-range night-time identification. We will describe an active-SWIR imaging system that is being developed to covertly detect, track, zoom in on, and positively identify a human target, night or day, at hundreds of meters range. The SWIR illuminator pans, tilts, and zooms with the imager to always just fill the imager field of view. The illuminator meets Class 1 eye-safety limits (safe even with magnifying optics) at the intended target, and meets Class 1M eye-safety limits (safe to the naked eye) at point-blank range. Close-up night-time facial imagery will be presented along with experimental face recognition performance results for matching SWIR imagery to a database of visible mug shots at distance. |
| Databáze: | OpenAIRE |
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