Most abandoned object detection algorithms proposed are either computationally intensive or weak in tracking abandoned object with occlusion. For this, an abandoned objects detection method under static cameras is presented based on dual backgrounds, which are updated with different strategies and frequencies. The background model is driven by accumulative average values instead of complex filters and hence it is simple and of lower computational cost. Besides, the algorithm is able to track abandoned objects under occlusion. Experimental results under the benchmark datasets on PET 2006 show that the proposed method has a good performance.