This chapter presents a novel background subtraction technique for detecting moving objects from video under dynamic background conditions. The presented methodology is a simple and low-cost solution for modeling and updating background during a background subtraction process. Comparative performance analysis with other state-of-the-art methods on benchmark data-set shows the effectiveness of the proposed method. The objective of the research is not to claim that the proposed method yields the best result in terms of accuracy; rather the main novelty is in its low computational cost. However, in spite of being less computation-intensive, comparative analysis reveals that the new method produces quite competitive results as compared to other methods. The proposed method would be useful particularly for applications in resource constrained environments by virtue of its low computation time and storage requirements. © The Author(s) 2014.