Abstract: In order to reduce the computational time and memory requirement of the existing dynamic background modeling methods，this paper presents a new background modeling and moving object detection method based on clustering.For a dynamic background，the histogram of each pixel value over time is usually in the form of multimodal.Therefore，regarding each peak as a cluster，clustering technique is employed to construct and update the model of a dynamic background.Then by using the established background model，the moving objects are segmented from the background quickly and accurately.Experimental results show that the proposed background modeling method can effectively capture and adapt to the changes in background.In addition，this method outperforms the current background modeling methods in terms of computational time and memory requirement，thus becoming easy to implement for DSP or FPGA based hardware.