关键词: 混合高斯模型, Kalman滤波, 目标检测, 背景更新

Abstract: In the current computer vision applications，the research on extracting moving objects from video sequences is very hot.Since the detection of moving objects can not be satisfactory with traditional methods，an improved mixture Gaussian background modeling method based on Kalman filtering theory is proposed.According to the characteristics of temporal recursive low pass of Kalman filtering，it is used to rectify the mixture Gaussian background model and improve the method of mixture Gaussian background modeling.Compared with traditional mixture Gaussian background model，the new method can eliminate system noise and inaccurate phenomenon that misjudges foreground as background when the lighting varies strongly.It improves the mixture Gaussian background model and makes it more reliable and robust.

Key words: mixture Gaussian model, Kalman filtering, objection detection, background update