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G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” Department of Computer Science University of North Carolina at Chapel Hill, 1997, pp. 27599-3175.

has been cited by the following article:

• TITLE: An Adaptive Particle Filter Based Method for Real Time Face Tracking

  AUTHORS: Wei-Ming Chen, Yi-Lung Lin, Ya-Hsiung Hsieh

  KEYWORDS: Particle Filter; Adaboost; Haar-Like Feature; SURF

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.6 No.5B, October 12, 2013

  ABSTRACT: The video surveillance systems of recent years, usually major focus on the Human-Face of observation and detection. Human-Face is the most characteristic and prominent feature of a human, therefore, detection and tracking of Human-Face has become an important indicator of the study. This paper discusses video surveillance of public places and majors inautomated face detection and face tracking. The main detection method is the use of Haar-Like Feature-based and through the Cascade classifier of the Adaboost face detection. In the tracking mechanism is based on particle filter and we modified SURF (Speeded Up Robust Features) particle filter tracking, and thus enhance the detection and tracking accuracy.