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Proceedings Paper

Video surveillance of passengers with mug shots
Author(s): Ming Kai Hsu; Ting N. Lee; Harold Szu
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Paper Abstract

The authority officer relies on facial mug-shots to spot suspects among crowds. Passing through a check point, the facial displays and printouts operate in low resolution fixed poses. Thus, a databases-cuing video is recommended for real-time surveillance with Aided-Target Recognition (AiTR) prompting the inspector taking a closer second look at a specific passenger. Taking advantage of commercial available Face Detection System on Chips (SOC) at 0.04sec, we develop a fast and smart algorithm to sort facial poses among passengers. We can increase the overlapping POFs (pixels on faces) in matching mug shots at arbitrary poses with sorted facial poses. Lemma: We define the long exposure as time average of facial poses and the short exposure as single facial pose in a frame of video in 30 Hz. The fiduciary triangle is defined among two eyes and nose-top. Theorem Self-Reference Matched Filtering (Szu et al. Opt Comm. 1980; JOSA, 1982) to Facial-Pose: If we replace the desirable output of Weiner filter as the long exposure, then the filter can select a short exposure as the normal view. Corollary: Given a short exposure as normal view, the fiduciary triangle can decide all poses from left-to-right and top-to-down.

Paper Details

Date Published: 12 April 2010
PDF: 9 pages
Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 770305 (12 April 2010); doi: 10.1117/12.850546
Show Author Affiliations
Ming Kai Hsu, The George Washington Univ. (United States)
Ting N. Lee, The George Washington Univ. (United States)
Harold Szu, U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 7703:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
Harold H. Szu; F. Jack Agee, Editor(s)

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