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Proceedings Paper

Video face recognition against a watch list
Author(s): Jehanzeb Abbas; Charlie K. Dagli; Thomas S. Huang
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Paper Abstract

Due to a large increase in the video surveillance data recently in an effort to maintain high security at public places, we need more robust systems to analyze this data and make tasks like face recognition a realistic possibility in challenging environments. In this paper we explore a watch-list scenario where we use an appearance based model to classify query faces from low resolution videos into either a watch-list or a non-watch-list face. We then use our simple yet a powerful face recognition system to recognize the faces classified as watch-list faces. Where the watch-list includes those people that we are interested in recognizing. Our system uses simple feature machine algorithms from our previous work to match video faces against still images. To test our approach, we match video faces against a large database of still images obtained from a previous work in the field from Yahoo News over a period of time. We do this matching in an efficient manner to come up with a faster and nearly real-time system. This system can be incorporated into a larger surveillance system equipped with advanced algorithms involving anomalous event detection and activity recognition. This is a step towards more secure and robust surveillance systems and efficient video data analysis.

Paper Details

Date Published: 8 October 2007
PDF: 8 pages
Proc. SPIE 6741, Optics and Photonics for Counterterrorism and Crime Fighting III, 67410F (8 October 2007); doi: 10.1117/12.736792
Show Author Affiliations
Jehanzeb Abbas, Univ. of Illinois at Urbana-Champaign (United States)
Charlie K. Dagli, Univ. of Illinois at Urbana-Champaign (United States)
Thomas S. Huang, Univ. of Illinois at Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 6741:
Optics and Photonics for Counterterrorism and Crime Fighting III
Colin Lewis, Editor(s)

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