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Object detection technologies have emerged as an important research area with increasing popularity of computer vision and camera devices. Even though several object detection approaches have been proposed, they cannot address various challenges in actual complex scenes owing to their applicability and restrictions. For the traditional Gaussian mixture model is sensitive to dynamic background, light change and shadow, an improved algorithm of Gaussian mixture model is proposed, which is used for object detection in video. Firstly, we extract rough region of the current frame by the traditional Gaussian mixed model. By introducing the two-level learning rate and combined weight into the Gaussian mixture model, the moving region and the background region containing the dynamic background are distinguished. Then shadow is removed based on color characteristic and spatial continuity. Finally, the complete and accurate moving object area is detected out by morphological closing operation. Comparative experiments indicate that the proposed method not only can effectively restrain the influence of dynamic background, but also suppress the influence of shadow and light changes.