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     This project developed an automated visual surveillance system which is an intelligent system based on computer vision technology and built for the security purpose to detect and track human intrusion and vandalism. Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments giving rise to the need of human detection.

 Graduate Students:

 Xiaoqian Xu

Publications:
  1. D.J. Lee, P. Zhan, A. Thomas, R.B. Schoenberger, ”Shape-based Human Intrusion Detection”, SPIE International Symposium on Defense and Security, Visual Information Processing XIII, vol. 5438, p. 81-91, Orlando, Florida, USA, April 12-16, 2004.

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