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朴大龍(Dae-Yong Park),金裁敏(Jae-Min Kim),趙成元(Seong-Won Cho) 대한전기학회 2006 전기학회논문지 D Vol.55 No.2
For the detection of moving objects, background subtraction methods are widely used. An adaptive Gaussian mixture model combined with probabilistic learning is one of the most popular methods for the real-time update of the complex and dynamic background. However, probabilistic learning approach does not work well in high traffic regions. In this paper, we propose a reliable learning method of complex and dynamic backgrounds in high traffic regions.